A Biochar Classification System and Associated Test Methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Camps-Arbestain, Marta; Amonette, James E.; Singh, Balwant

2015-02-18

In this chapter, a biochar classification system related to its use as soil amendment is proposed. This document builds upon previous work and constrains its scope to materials with properties that satisfy the criteria for biochar as defined by either the International Biochar Initiative (IBI) Biochar Standards or the European Biochar Community (EBC) Standards, and it is intended to minimise the need for testing in addition to those required according to the above-mentioned standards. The classification system envisions enabling stakeholders and commercial entities to (i) identify the most suitable biochar to fulfil the requirements for a particular soil and/or land-use,more » and (ii) distinguish the application of biochar for specific niches (e.g., soilless agriculture). It is based on the best current knowledge and the intention is to periodically review and update the document based on new data and knowledge that become available in the scientific literature. The main thrust of this classification system is based on the direct or indirect beneficial effects that biochar provides from its application to soil. We have classified the potential beneficial effects of biochar application to soils into five categories with their corresponding classes, where applicable: (i) carbon (C) storage value, (ii) fertiliser value, (iii) liming value, (iv) particle-size, and (v) use in soil-less agriculture. A summary of recommended test methods is provided at the end of the chapter.« less

The History of Soil Mapping and Classification in Europe: The role of the European Commission

NASA Astrophysics Data System (ADS)

Montanarella, Luca

2014-05-01

Early systematic soil mapping in Europe dates back to the early times of soil science in the 19th Century and was developed at National scales mostly for taxation purposes. National soil classification systems emerged out of the various scientific communities active at that time in leading countries like Germany, Austria, France, Belgium, United Kingdom and many others. Different scientific communities were leading in the various countries, in some cases stemming from geological sciences, in others as a branch of agricultural sciences. Soil classification for the purpose of ranking soils for their capacity to be agriculturally productive emerged as the main priority, allowing in some countries for very detailed and accurate soil maps at 1:5,000 scale and larger. Detailed mapping was mainly driven by taxation purposes in the early times but evolved in several countries also as a planning and management tool for farms and local administrations. The need for pan-European soil mapping and classification efforts emerged only after World War II in the early 1950's under the auspices of FAO with the aim to compile a common European soil map as a contribution to the global soil mapping efforts of FAO at that time. These efforts evolved over the next decades, with the support of the European Commission, towards the establishment of a permanent network of National soil survey institutions (the European Soil Bureau Network). With the introduction of digital soil mapping technologies, the new European Soil Information System (EUSIS) was established, incorporating data at multiple scales for the EU member states and bordering countries. In more recent years, the formal establishment of the European Soil Data Centre (ESDAC) hosted by the European Commission, together with a formal legal framework for soil mapping and soil classification provided by the INSPIRE directive and the related standardization and harmonization efforts, has led to the operational development of advanced digital soil mapping techniques supporting the contribution of Europe to a common global soil information system under the coordination of the Global Soil Partnership (GSP) of FAO. Further information: http://eusoils.jrc.ec.europa.eu/ References: Mark G Kibblewhite, Ladislav Miko, Luca Montanarella, Legal frameworks for soil protection: current development and technical information requirements, Current Opinion in Environmental Sustainability, Volume 4, Issue 5, November 2012, Pages 573-577. Luca Montanarella, Ronald Vargas, Global governance of soil resources as a necessary condition for sustainable development, Current Opinion in Environmental Sustainability, Volume 4, Issue 5, November 2012, Pages 559-564.

[Extracting black soil border in Heilongjiang province based on spectral angle match method].

PubMed

Zhang, Xin-Le; Zhang, Shu-Wen; Li, Ying; Liu, Huan-Jun

2009-04-01

As soils are generally covered by vegetation most time of a year, the spectral reflectance collected by remote sensing technique is from the mixture of soil and vegetation, so the classification precision based on remote sensing (RS) technique is unsatisfied. Under RS and geographic information systems (GIS) environment and with the help of buffer and overlay analysis methods, land use and soil maps were used to derive regions of interest (ROI) for RS supervised classification, which plus MODIS reflectance products were chosen to extract black soil border, with methods including spectral single match. The results showed that the black soil border in Heilongjiang province can be extracted with soil remote sensing method based on MODIS reflectance products, especially in the north part of black soil zone; the classification precision of spectral angel mapping method is the highest, but the classifying accuracy of other soils can not meet the need, because of vegetation covering and similar spectral characteristics; even for the same soil, black soil, the classifying accuracy has obvious spatial heterogeneity, in the north part of black soil zone in Heilongjiang province it is higher than in the south, which is because of spectral differences; as soil uncovering period in Northeastern China is relatively longer, high temporal resolution make MODIS images get the advantage over soil remote sensing classification; with the help of GIS, extracting ROIs by making the best of auxiliary data can improve the precision of soil classification; with the help of auxiliary information, such as topography and climate, the classification accuracy was enhanced significantly. As there are five main factors determining soil classes, much data of different types, such as DEM, terrain factors, climate (temperature, precipitation, etc.), parent material, vegetation map, and remote sensing images, were introduced to classify soils, so how to choose some of the data and quantify the weights of different data layers needs further study.

Guidance for Determining the Acceptability of Environmental Fate Studies Conducted with Foreign Soils

EPA Pesticide Factsheets

International and U.S. soil taxonomical classification systems, distribution of soil orders in the United States, specific criteria to help scientists determine when foreign soils are representative of U.S. soils at intended pesticide use sites.

Transfer of the nationwide Czech soil survey data to a foreign soil classification - generating input parameters for a process-based soil erosion modelling approach

NASA Astrophysics Data System (ADS)

Beitlerová, Hana; Hieke, Falk; Žížala, Daniel; Kapička, Jiří; Keiser, Andreas; Schmidt, Jürgen; Schindewolf, Marcus

2017-04-01

Process-based erosion modelling is a developing and adequate tool to assess, simulate and understand the complex mechanisms of soil loss due to surface runoff. While the current state of available models includes powerful approaches, a major drawback is given by complex parametrization. A major input parameter for the physically based soil loss and deposition model EROSION 3D is represented by soil texture. However, as the model has been developed in Germany it is dependent on the German soil classification. To exploit data generated during a massive nationwide soil survey campaign taking place in the 1960s across the entire Czech Republic, a transfer from the Czech to the German or at least international (e.g. WRB) system is mandatory. During the survey the internal differentiation of grain sizes was realized in a two fractions approach, separating texture into solely above and below 0.01 mm rather than into clayey, silty and sandy textures. Consequently, the Czech system applies a classification of seven different textures based on the respective percentage of large and small particles, while in Germany 31 groups are essential. The followed approach of matching Czech soil survey data to the German system focusses on semi-logarithmic interpolation of the cumulative soil texture curve additionally on a regression equation based on a recent database of 128 soil pits. Furthermore, for each of the seven Czech texture classes a group of typically suitable classes of the German system was derived. A GIS-based spatial analysis to test approaches of interpolation the soil texture was carried out. First results show promising matches and pave the way to a Czech model application of EROSION 3D.

Ethnopedology and soil quality of bamboo (Bambusa sp.) based agroforestry system.

PubMed

Arun Jyoti, Nath; Lal, Rattan; Das, Ashesh Kumar

2015-07-15

It is widely recognized that farmers' hold important knowledge of folk soil classification for agricultural land for its uses, yet little has been studied for traditional agroforestry systems. This article explores the ethnopedology of bamboo (Bambusa sp.) based agroforestry system in North East India, and establishes the relationship of soil quality index (SQI) with bamboo productivity. The study revealed four basic folk soil (mati) types: kalo (black soil), lal (red soil), pathal (stony soil) and balu (sandy soil). Of these, lal mati soil was the most predominant soil type (~ 40%) in bamboo-based agroforestry system. Soil physio-chemical parameters were studied to validate the farmers' soil hierarchal classification and also to correlate with productivity of the bamboo stand. Farmers' hierarchal folk soil classification was consistent with the laboratory scientific analysis. Culm production (i.e. measure of productivity of bamboo) was the highest (27culmsclump(-1)) in kalo mati (black soil) and the lowest (19culmsclump(-1)) in balu mati (sandy soil). Linear correlation of individual soil quality parameter with bamboo productivity explained 16 to 49% of the variability. A multiple correlation of the best fitted linear soil quality parameter (soil organic carbon or SOC, water holding capacity or WHC, total nitrogen) with productivity improved explanatory power to 53%. Development of SQI from ten relevant soil quality parameters and its correlation with bamboo productivity explained the 64% of the variation and therefore, suggest SQI as the best determinant of bamboo yield. Data presented indicate that the kalo mati (black soil) is sustainable or sustainable with high input. However, the other three folk soil types (red, stony and sandy soil) are also sustainable but for other land uses. Therefore, ethnopedological studies may move beyond routine laboratory analysis and incorporate SQI for assessing the sustainability of land uses managed by the farmers'. Additional research is required to incorporate principal component analysis for improving the SQI and site potential assessment. It is also important to evaluate the minimum data set (MDS) required for SQI and productivity assessment in agroforestry systems. Copyright © 2015 Elsevier B.V. All rights reserved.

24 CFR 3285.202 - Soil classifications and bearing capacity.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 24 Housing and Urban Development 5 2010-04-01 2010-04-01 false Soil classifications and bearing... Soil classifications and bearing capacity. The soil classification and bearing capacity of the soil must be determined before the foundation is constructed and anchored. The soil classification and...

24 CFR 3285.202 - Soil classifications and bearing capacity.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 24 Housing and Urban Development 5 2014-04-01 2014-04-01 false Soil classifications and bearing... Soil classifications and bearing capacity. The soil classification and bearing capacity of the soil must be determined before the foundation is constructed and anchored. The soil classification and...

24 CFR 3285.202 - Soil classifications and bearing capacity.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 24 Housing and Urban Development 5 2012-04-01 2012-04-01 false Soil classifications and bearing... Soil classifications and bearing capacity. The soil classification and bearing capacity of the soil must be determined before the foundation is constructed and anchored. The soil classification and...

24 CFR 3285.202 - Soil classifications and bearing capacity.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 24 Housing and Urban Development 5 2013-04-01 2013-04-01 false Soil classifications and bearing... Soil classifications and bearing capacity. The soil classification and bearing capacity of the soil must be determined before the foundation is constructed and anchored. The soil classification and...

24 CFR 3285.202 - Soil classifications and bearing capacity.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 24 Housing and Urban Development 5 2011-04-01 2011-04-01 false Soil classifications and bearing... Soil classifications and bearing capacity. The soil classification and bearing capacity of the soil must be determined before the foundation is constructed and anchored. The soil classification and...

An ecological classification system for the central hardwoods region: The Hoosier National Forest

Treesearch

James E. Van Kley; George R. Parker

1993-01-01

This study, a multifactor ecological classification system, using vegetation, soil characteristics, and physiography, was developed for the landscape of the Hoosier National Forest in Southern Indiana. Measurements of ground flora, saplings, and canopy trees from selected stands older than 80 years were subjected to TWINSPAN classification and DECORANA ordination....

Classification and evaluation for forest sites on the Mid-Cumberland Plateau

Treesearch

Glendon W. Smalley

1982-01-01

Presents a comprehensive forest site classification system for the central portion of the Cumberland Plateau in northeast Alabama, and east-central Tennessee. The system is based on physiography, geology, soils, topography, and vegetation.

Soils and the soil cover of the Valley of Geysers

NASA Astrophysics Data System (ADS)

Kostyuk, D. N.; Gennadiev, A. N.

2014-06-01

The results of field studies of the soil cover within the tourist part of the Valley of Geysers in Kamchatka performed in 2010 and 2011 are discussed. The morphology of soils, their genesis, and their dependence on the degree of hydrothermal impact are characterized; the soil cover patterns developing in the valley are analyzed. On the basis of the materials provided by the Kronotskii Biospheric Reserve and original field data, the soil map of the valley has been developed. The maps of vegetation conditions, soil temperature at the depth of 15 cm, and slopes of the surface have been used for this purpose together with satellite imagery and field descriptions of reference soil profiles. The legend to the soil map includes nine soil units and seven units of parent materials and their textures. Soil names are given according to the classification developed by I.L. Goldfarb (2005) for the soils of hydrothermal fields. The designation of soil horizons follows the new Classification and Diagnostic System of Russian Soils (2004). It is suggested that a new horizon—a thermometamorphic horizon TRM—can be introduced into this system by analogy with other metamorphic (transformed in situ) horizons distinguished in this system. This horizon is typical of the soils partly or completely transformed by hydrothermal impacts.

Principles of soil mapping of a megalopolis with St. Petersburg as an example

NASA Astrophysics Data System (ADS)

Aparin, B. F.; Sukhacheva, E. Yu.

2014-07-01

For the first time, a soil map of St. Petersburg has been developed on a scale of 1 : 50000 using MicroStation V8i software. The legend to this map contains more than 60 mapping units. The classification of urban soils and information on the soil cover patterns are principally new elements of this legend. New concepts of the urbanized soil space and urbopedocombinations have been suggested for soil mapping of urban territories. The typification of urbopedocombinations in St. Petersburg has been performed on the basis of data on the geometry and composition of the polygons of soils and nonsoil formations. The ratio between the areas of soils and nonsoil formations and their spatial distribution patterns have been used to distinguish between six types of the urbanized soil space. The principles of classification of the soils of urban territories have been specified, and a separate order of pedo-allochthonous soils has been suggested for inclusion into the Classification and Diagnostic System of Russian Soils (2004). Six types of pedo-allochthonous soils have been distinguished on the basis of data on their humus and organic horizons and the character of the underlying mineral substrate.

Methods for Tier 1 Modeling within the Training Range Environmental Evaluation and Characterization System

DTIC Science & Technology

2009-08-01

properties, part b. USLE K-Factor by Organic Matter Content Soil -Texture Classification Dry Bulk Density, g/cm3 Field Capacity, % Available...Universal Soil Loss Equation ( USLE ) can be used to estimate annual average sheet and rill erosion, A (tons/acre-yr), from the equation A R K L S...erodibility factors, K, for various soil classifications and percent organic matter content ( USLE Fact Sheet 2008). Textural Class Average Less than 2

Soil Taxonomy and land evaluation for forest establishment

Treesearch

Haruyoshi Ikawa

1992-01-01

Soil Taxonomy, the United States system of soil classification, can be used for land evaluation for selected purposes. One use is forest establishment in the tropics, and the soil family category is especially functional for this purpose. The soil family is a bionomial name with descriptions usually of soil texture, mineralogy, and soil temperature classes. If the...

Sensitivity analysis of the GEMS soil organic carbon model to land cover land use classification uncertainties under different climate scenarios in Senegal

USGS Publications Warehouse

Dieye, A.M.; Roy, David P.; Hanan, N.P.; Liu, S.; Hansen, M.; Toure, A.

2012-01-01

Spatially explicit land cover land use (LCLU) change information is needed to drive biogeochemical models that simulate soil organic carbon (SOC) dynamics. Such information is increasingly being mapped using remotely sensed satellite data with classification schemes and uncertainties constrained by the sensing system, classification algorithms and land cover schemes. In this study, automated LCLU classification of multi-temporal Landsat satellite data were used to assess the sensitivity of SOC modeled by the Global Ensemble Biogeochemical Modeling System (GEMS). The GEMS was run for an area of 1560 km2 in Senegal under three climate change scenarios with LCLU maps generated using different Landsat classification approaches. This research provides a method to estimate the variability of SOC, specifically the SOC uncertainty due to satellite classification errors, which we show is dependent not only on the LCLU classification errors but also on where the LCLU classes occur relative to the other GEMS model inputs.

Classification and evaluation for forest sites on the Eastern Highland Rim and Pennyroyal.

Treesearch

Glendon W. Smalley

1983-01-01

Presents a comprehensive forest site classification system for the Eastern Highland Rim and Pennyroyal in north Alabama, east-central Tennessee, and central Kentucky. The system is based on physiography, geology, soils, topography, and vegetation.

Classification and evaluation for forest sites on the Western Highland Rim and Pennyroyal

Treesearch

Glendon W. Smalley

1980-01-01

Presents a comprehensive forest site classification system for the Western Highland Rim and Western Pennyroyal-Limestone area in northwest Alabama, west-central Tennessee, and western Kentucky. The system is based on physiography, geology, soils, topography, and vegetation.

[Classification of Priority Area for Soil Environmental Protection Around Water Sources: Method Proposed and Case Demonstration].

PubMed

Li, Lei; Wang, Tie-yu; Wang, Xiaojun; Xiao, Rong-bo; Li, Qi-feng; Peng, Chi; Han, Cun-liang

2016-04-15

Based on comprehensive consideration of soil environmental quality, pollution status of river, environmental vulnerability and the stress of pollution sources, a technical method was established for classification of priority area of soil environmental protection around the river-style water sources. Shunde channel as an important drinking water sources of Foshan City, Guangdong province, was studied as a case, of which the classification evaluation system was set up. In detail, several evaluation factors were selected according to the local conditions of nature, society and economy, including the pollution degree of heavy metals in soil and sediment, soil characteristics, groundwater sensitivity, vegetation coverage, the type and location of pollution sources. Data information was mainly obtained by means of field survey, sampling analysis, and remote sensing interpretation. Afterwards, Analytical Hierarchy Process (AHP) was adopted to decide the weight of each factor. The basic spatial data layers were set up respectively and overlaid based on the weighted summation assessment model in Geographical Information System (GIS), resulting in a classification map of soil environmental protection level in priority area of Shunde channel. Accordingly, the area was classified to three levels named as polluted zone, risky zone and safe zone, which respectively accounted for 6.37%, 60.90% and 32.73% of the whole study area. Polluted zone and risky zone were mainly distributed in Lecong, Longjiang and Leliu towns, with pollutants mainly resulted from the long-term development of aquaculture and the industries containing furniture, plastic constructional materials and textile and clothing. In accordance with the main pollution sources of soil, targeted and differentiated strategies were put forward. The newly established evaluation method could be referenced for the protection and sustainable utilization of soil environment around the water sources.

Fire severity classification: Uses and abuses

Treesearch

Theresa B. Jain; Russell T. Graham

2003-01-01

Burn severity (also referred to as fire severity) is not a single definition, but rather a concept and its classification is a function of the measured units unique to the system of interest. The systems include: flora and fauna, soil microbiology and hydrologic processes, atmospheric inputs, fire management, and society. Depending on the particular system of interest...

Semi-automated landform classification for hazard mapping of soil liquefaction by earthquake

NASA Astrophysics Data System (ADS)

Nakano, Takayuki

2018-05-01

Soil liquefaction damages were caused by huge earthquake in Japan, and the similar damages are concerned in near future huge earthquake. On the other hand, a preparation of soil liquefaction risk map (soil liquefaction hazard map) is impeded by the difficulty of evaluation of soil liquefaction risk. Generally, relative soil liquefaction risk should be able to be evaluated from landform classification data by using experimental rule based on the relationship between extent of soil liquefaction damage and landform classification items associated with past earthquake. Therefore, I rearranged the relationship between landform classification items and soil liquefaction risk intelligibly in order to enable the evaluation of soil liquefaction risk based on landform classification data appropriately and efficiently. And I developed a new method of generating landform classification data of 50-m grid size from existing landform classification data of 250-m grid size by using digital elevation model (DEM) data and multi-band satellite image data in order to evaluate soil liquefaction risk in detail spatially. It is expected that the products of this study contribute to efficient producing of soil liquefaction hazard map by local government.

Project implementation : classification of organic soils and classification of marls - training of INDOT personnel.

DOT National Transportation Integrated Search

2012-09-01

This is an implementation project for the research completed as part of the following projects: SPR3005 Classification of Organic Soils : and SPR3227 Classification of Marl Soils. The methods developed for the classification of both soi...

Use of an automatic procedure for determination of classes of land use in the Teste Araras area of the peripheral Paulist depression

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Lombardo, M. A.; Valeriano, D. D.

1981-01-01

An evaluation of the multispectral image analyzer (system Image 1-100), using automatic classification, is presented. The region studied is situated. The automatic was carried out using the maximum likelihood (MAXVER) classification system. The following classes were established: urban area, bare soil, sugar cane, citrus culture (oranges), pastures, and reforestation. The classification matrix of the test sites indicate that the percentage of correct classification varied between 63% and 100%.

Hydrologic-Process-Based Soil Texture Classifications for Improved Visualization of Landscape Function

PubMed Central

Groenendyk, Derek G.; Ferré, Ty P.A.; Thorp, Kelly R.; Rice, Amy K.

2015-01-01

Soils lie at the interface between the atmosphere and the subsurface and are a key component that control ecosystem services, food production, and many other processes at the Earth’s surface. There is a long-established convention for identifying and mapping soils by texture. These readily available, georeferenced soil maps and databases are used widely in environmental sciences. Here, we show that these traditional soil classifications can be inappropriate, contributing to bias and uncertainty in applications from slope stability to water resource management. We suggest a new approach to soil classification, with a detailed example from the science of hydrology. Hydrologic simulations based on common meteorological conditions were performed using HYDRUS-1D, spanning textures identified by the United States Department of Agriculture soil texture triangle. We consider these common conditions to be: drainage from saturation, infiltration onto a drained soil, and combined infiltration and drainage events. Using a k-means clustering algorithm, we created soil classifications based on the modeled hydrologic responses of these soils. The hydrologic-process-based classifications were compared to those based on soil texture and a single hydraulic property, Ks. Differences in classifications based on hydrologic response versus soil texture demonstrate that traditional soil texture classification is a poor predictor of hydrologic response. We then developed a QGIS plugin to construct soil maps combining a classification with georeferenced soil data from the Natural Resource Conservation Service. The spatial patterns of hydrologic response were more immediately informative, much simpler, and less ambiguous, for use in applications ranging from trafficability to irrigation management to flood control. The ease with which hydrologic-process-based classifications can be made, along with the improved quantitative predictions of soil responses and visualization of landscape function, suggest that hydrologic-process-based classifications should be incorporated into environmental process models and can be used to define application-specific maps of hydrologic function. PMID:26121466

Hydrologic-Process-Based Soil Texture Classifications for Improved Visualization of Landscape Function.

PubMed

Groenendyk, Derek G; Ferré, Ty P A; Thorp, Kelly R; Rice, Amy K

2015-01-01

Soils lie at the interface between the atmosphere and the subsurface and are a key component that control ecosystem services, food production, and many other processes at the Earth's surface. There is a long-established convention for identifying and mapping soils by texture. These readily available, georeferenced soil maps and databases are used widely in environmental sciences. Here, we show that these traditional soil classifications can be inappropriate, contributing to bias and uncertainty in applications from slope stability to water resource management. We suggest a new approach to soil classification, with a detailed example from the science of hydrology. Hydrologic simulations based on common meteorological conditions were performed using HYDRUS-1D, spanning textures identified by the United States Department of Agriculture soil texture triangle. We consider these common conditions to be: drainage from saturation, infiltration onto a drained soil, and combined infiltration and drainage events. Using a k-means clustering algorithm, we created soil classifications based on the modeled hydrologic responses of these soils. The hydrologic-process-based classifications were compared to those based on soil texture and a single hydraulic property, Ks. Differences in classifications based on hydrologic response versus soil texture demonstrate that traditional soil texture classification is a poor predictor of hydrologic response. We then developed a QGIS plugin to construct soil maps combining a classification with georeferenced soil data from the Natural Resource Conservation Service. The spatial patterns of hydrologic response were more immediately informative, much simpler, and less ambiguous, for use in applications ranging from trafficability to irrigation management to flood control. The ease with which hydrologic-process-based classifications can be made, along with the improved quantitative predictions of soil responses and visualization of landscape function, suggest that hydrologic-process-based classifications should be incorporated into environmental process models and can be used to define application-specific maps of hydrologic function.

Dynamic Response of Reinforced Soil Systems. Volume 1. Report

DTIC Science & Technology

1993-03-01

include Security Clas~sification) DYNAMIC RWSPC!SE OF REIFý1Cý SOIL SYSTEM~, VCTJI4E I OF II: PREPO~r 󈧐. PERSONAL AUTHOR($) BMW3U, R.C.; FRAWASZY...protected by a burster slab. These protection measures are costly, time consuming to construct, and sensitive to multiple strikes. Soil has been used to...characterize the static load-deflection behavior of the reinforced soil. Dynamic pullout tests were then performed using the same parameters as the static

Digital soil map of the Ussuri River basin

NASA Astrophysics Data System (ADS)

Bugaets, A. N.; Pschenichnikova, N. F.; Tereshkina, A. A.; Krasnopeev, S. M.; Gartsman, B. I.; Golodnaya, O. M.; Oznobikhin, V. I.

2017-08-01

On the basis of digital soil, topographic, and geological maps; raster topography model; forestry materials; and literature data, the digital soil map of the Ussuri River basin (24400 km2) was created on a scale of 1: 100000. To digitize the initial paper-based maps and analyze the results, an ESRI ArcGIS Desktop (ArcEditor) v.10.1 (http://www.esri.com) and an open-code SAGA GIS v.2.3 (System for Automated Geoscientific Analyses, http://www.saga-gis.org) were used. The spatial distribution of soil areas on the obtained digital soil map is in agreement with modern cartographic data and the SRTM digital elevation model (SRTM DEM). The regional soil classification developed by G.I. Ivanov was used in the legend to the soil map. The names of soil units were also correlated with the names suggested in the modern Russian soil classification system. The major soil units on the map are at the soil subtypes that reflect the entire vertical spectrum of soils in the south of the Far East of Russia (Primorye region). These are mountainous tundra soils, podzolic soils, brown taiga soils, mountainous brown forest soils, bleached brown soils, meadow-brown soils, meadow gley soils, and floodplain soils). With the help of the spatial analysis function of GIS, the comparison of the particular characteristics of the soil cover with numerical characteristics of the topography, geological composition of catchments, and vegetation cover was performed.

Classification and evaluation for forest sites on the Southern Cumberland Plateau

Treesearch

Glendon W. Smalley

1979-01-01

This paper presents a comprehensive forest site classification system for the southern portion of the Cumberland Plateau in northern Alabama, northwest Georgia, and extreme south-central Tennessee. The system is based on physiography, geology, soils, topography, and vegetation. Twenty-one landtypes are described, and each landtype is evaluated in terms of productivity...

Selected Aspects of Soil Science History in the USA - Prehistory to the 1970s

NASA Astrophysics Data System (ADS)

Brevik, Eric C.; Fenton, Thomas E.; Homburg, Jeffrey A.

2017-04-01

Interest in understanding America's soils originated in prehistory with Native Americans. Following European settlement, notable individuals such as Thomas Jefferson and Lewis and Clark made observations of soil resources. Moving into the 1800s, state geological surveys became involved in soil work and E.W. Hilgard started to formulate ideas similar to those that would eventually lead to V.V. Dokuchaev being recognized as the father of modern soil science. However, Hilgard's advanced ideas on soil genesis were not accepted by the wider American soil science community at the time. Moving into the 1900s, the National Cooperative Soil Survey, the first nationally organized detailed soil survey in the world, was founded under the direction of M. Whitney. Initial soil classification ideas were heavily based in geology, but over time Russian ideas of soil genesis and classification moved into the American soil science community, mainly due to the influence of C.F. Marbut. Early American efforts in scientific study of soil erosion and soil fertility were also initiated in the 1910s and university programs to educate soil scientists started. Soil erosion studies took on high priority in the 1930s as the USA was impacted by the Dust Bowl. Soil Taxonomy, one of the most widely utilized soil classification systems in the world, was developed from the 1950s through the 1970s under the guidance of G.D. Smith and with administrative support from C.E. Kellogg. American soil scientists, such as H. Jenny, R.W. Simonson, D.L. Johnson, and D. Watson-Stegner, developed influential models of soil genesis during the 20th Century, and the use of soil information expanded beyond agriculture to include issues such as land-use planning, soil geomorphology, and interactions between soils and human health.

Particle-size distribution models for the conversion of Chinese data to FAO/USDA system.

PubMed

Shangguan, Wei; Dai, YongJiu; García-Gutiérrez, Carlos; Yuan, Hua

2014-01-01

We investigated eleven particle-size distribution (PSD) models to determine the appropriate models for describing the PSDs of 16349 Chinese soil samples. These data are based on three soil texture classification schemes, including one ISSS (International Society of Soil Science) scheme with four data points and two Katschinski's schemes with five and six data points, respectively. The adjusted coefficient of determination r (2), Akaike's information criterion (AIC), and geometric mean error ratio (GMER) were used to evaluate the model performance. The soil data were converted to the USDA (United States Department of Agriculture) standard using PSD models and the fractal concept. The performance of PSD models was affected by soil texture and classification of fraction schemes. The performance of PSD models also varied with clay content of soils. The Anderson, Fredlund, modified logistic growth, Skaggs, and Weilbull models were the best.

Occurrence of shale soils along the Calabar-Itu highway, Southeastern Nigeria and their implication for the subgrade construction.

PubMed

Ilori, Abidemi Olujide

2016-01-01

This study concerned a stretch of 17 km of a 94-km highway alignment in Southeastern Nigeria that has a high incidence of pavement failure arising from subgrade failure. The subgrade of this section of the roadway is composed of Ekenkpon shale, New Netim marl, and Nkporo shale. Under the Unified Soil Classification System, the shales classify as OH (organic clay) and the marl classifies as MH (inorganic silt). Under the American Association of State and Transportation Officials (AASHTO) M 145 soil classification, all these soils classify as A-7-5 soil. Using the AASHTO M 145 group index, none of these soils was considered suitable as subgrade in its native form. Therefore, cement was investigated as a stabilizing agent. Testing demonstrated that 7, 3 and 12 % by weight were the optimum cement contents to reinforce the Ekenkpon shale, New Netim marl, and Nkporo shale, respectively.

An alternative to soil taxonomy for describing key soil characteristics

USGS Publications Warehouse

Duniway, Michael C.; Miller, Mark E.; Brown, Joel R.; Toevs, Gordon

2013-01-01

is not a simple task. Furthermore, because the US system of soil taxonomy is not applied universally, its utility as a means for effectively describing soil characteristics to readers in other countries is limited. Finally, and most importantly, even at the finest level of soil classification there are often large within-taxa variations in critical properties that can determine ecosystem responses to drivers such as climate and land-use change.

Soil classification based on cone penetration test (CPT) data in Western Central Java

NASA Astrophysics Data System (ADS)

Apriyono, Arwan; Yanto, Santoso, Purwanto Bekti; Sumiyanto

2018-03-01

This study presents a modified friction ratio range for soil classification i.e. gravel, sand, silt & clay and peat, using CPT data in Western Central Java. The CPT data was obtained solely from Soil Mechanic Laboratory of Jenderal Soedirman University that covers more than 300 sites within the study area. About 197 data were produced from data filtering process. IDW method was employed to interpolated friction ratio values in a regular grid point for soil classification map generation. Soil classification map was generated and presented using QGIS software. In addition, soil classification map with respect to modified friction ratio range was validated using 10% of total measurements. The result shows that silt and clay dominate soil type in the study area, which is in agreement with two popular methods namely Begemann and Vos. However, the modified friction ratio range produces 85% similarity with laboratory measurements whereby Begemann and Vos method yields 70% similarity. In addition, modified friction ratio range can effectively distinguish fine and coarse grains, thus useful for soil classification and subsequently for landslide analysis. Therefore, modified friction ratio range proposed in this study can be used to identify soil type for mountainous tropical region.

29 CFR Appendix A to Subpart P of... - Soil Classification

Code of Federal Regulations, 2013 CFR

2013-07-01

... 29 Labor 8 2013-07-01 2013-07-01 false Soil Classification A Appendix A to Subpart P of Part 1926..., App. A Appendix A to Subpart P of Part 1926—Soil Classification (a) Scope and application—(1) Scope. This appendix describes a method of classifying soil and rock deposits based on site and environmental...

29 CFR Appendix A to Subpart P of... - Soil Classification

Code of Federal Regulations, 2012 CFR

2012-07-01

... 29 Labor 8 2012-07-01 2012-07-01 false Soil Classification A Appendix A to Subpart P of Part 1926..., App. A Appendix A to Subpart P of Part 1926—Soil Classification (a) Scope and application—(1) Scope. This appendix describes a method of classifying soil and rock deposits based on site and environmental...

29 CFR Appendix A to Subpart P of... - Soil Classification

Code of Federal Regulations, 2014 CFR

2014-07-01

... 29 Labor 8 2014-07-01 2014-07-01 false Soil Classification A Appendix A to Subpart P of Part 1926..., App. A Appendix A to Subpart P of Part 1926—Soil Classification (a) Scope and application—(1) Scope. This appendix describes a method of classifying soil and rock deposits based on site and environmental...

29 CFR Appendix A to Subpart P of... - Soil Classification

Code of Federal Regulations, 2011 CFR

2011-07-01

... 29 Labor 8 2011-07-01 2011-07-01 false Soil Classification A Appendix A to Subpart P of Part 1926..., App. A Appendix A to Subpart P of Part 1926—Soil Classification (a) Scope and application—(1) Scope. This appendix describes a method of classifying soil and rock deposits based on site and environmental...

Test Operation Procedure (TOP) 01-1-010A Vehicle Test Course Severity (Surface Roughness)

DTIC Science & Technology

2017-12-12

Department of Agriculture (USDA) classifications, respectively. TABLE 10. PARTICLE SIZE CLASSES CLASS SIZE Cobble and Gravel >4.75 mm particle diameter...ABBREVIATIONS. USCS Unified Soil Classification System USDA United States Department of Agriculture UTM Universal Transverse Mercator WNS wave number

Comparing the performance of various digital soil mapping approaches to map physical soil properties

NASA Astrophysics Data System (ADS)

Laborczi, Annamária; Takács, Katalin; Pásztor, László

2015-04-01

Spatial information on physical soil properties is intensely expected, in order to support environmental related and land use management decisions. One of the most widely used properties to characterize soils physically is particle size distribution (PSD), which determines soil water management and cultivability. According to their size, different particles can be categorized as clay, silt, or sand. The size intervals are defined by national or international textural classification systems. The relative percentage of sand, silt, and clay in the soil constitutes textural classes, which are also specified miscellaneously in various national and/or specialty systems. The most commonly used is the classification system of the United States Department of Agriculture (USDA). Soil texture information is essential input data in meteorological, hydrological and agricultural prediction modelling. Although Hungary has a great deal of legacy soil maps and other relevant soil information, it often occurs, that maps do not exist on a certain characteristic with the required thematic and/or spatial representation. The recent developments in digital soil mapping (DSM), however, provide wide opportunities for the elaboration of object specific soil maps (OSSM) with predefined parameters (resolution, accuracy, reliability etc.). Due to the simultaneous richness of available Hungarian legacy soil data, spatial inference methods and auxiliary environmental information, there is a high versatility of possible approaches for the compilation of a given soil map. This suggests the opportunity of optimization. For the creation of an OSSM one might intend to identify the optimum set of soil data, method and auxiliary co-variables optimized for the resources (data costs, computation requirements etc.). We started comprehensive analysis of the effects of the various DSM components on the accuracy of the output maps on pilot areas. The aim of this study is to compare and evaluate different digital soil mapping methods and sets of ancillary variables for producing the most accurate spatial prediction of texture classes in a given area of interest. Both legacy and recently collected data on PSD were used as reference information. The predictor variable data set consisted of digital elevation model and its derivatives, lithology, land use maps as well as various bands and indices of satellite images. Two conceptionally different approaches can be applied in the mapping process. Textural classification can be realized after particle size data were spatially extended by proper geostatistical method. Alternatively, the textural classification is carried out first, followed by the spatial extension through suitable data mining method. According to the first approach, maps of sand, silt and clay percentage have been computed through regression kriging (RK). Since the three maps are compositional (their sum must be 100%), we applied Additive Log-Ratio (alr) transformation, instead of kriging them independently. Finally, the texture class map has been compiled according to the USDA categories from the three maps. Different combinations of reference and training soil data and auxiliary covariables resulted several different maps. On the basis of the other way, the PSD were classified firstly into the USDA categories, then the texture class maps were compiled directly by data mining methods (classification trees and random forests). The various results were compared to each other as well as to the RK maps. The performance of the different methods and data sets has been examined by testing the accuracy of the geostatistically computed and the directly classified results to assess the most predictive and accurate method. Acknowledgement: Our work was supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).

Coast redwood ecological types of southern Monterey County, California

Treesearch

Mark Borchert; Daniel Segotta; Michael D. Purser

1988-01-01

An ecological classification system has been developed for the Pacific Southwest Region of the Forest Service. As part of this classification effort, coast redwood (Sequoia sempervirens) forests of southern Monterey County in the Los Padres National Forest were classified into six ecological types using vegetation, soils and geomorphology taken from...

Is the textural classification built on sand?

USDA-ARS?s Scientific Manuscript database

In 1967, the Committee of the Soil Science Society of America noted that the current system of particle size boundaries arose due to geographic accident. The committee noted that there is “no narrowly defineable natural particle size boundaries that would be equally significant in all soil materials...

SOIL Geo-Wiki: A tool for improving soil information

NASA Astrophysics Data System (ADS)

Skalský, Rastislav; Balkovic, Juraj; Fritz, Steffen; See, Linda; van der Velde, Marijn; Obersteiner, Michael

2014-05-01

Crowdsourcing is increasingly being used as a way of collecting data for scientific research, e.g. species identification, classification of galaxies and unravelling of protein structures. The WorldSoilProfiles.org database at ISRIC is a global collection of soil profiles, which have been 'crowdsourced' from experts. This system, however, requires contributors to have a priori knowledge about soils. Yet many soil parameters can be observed in the field without specific knowledge or equipment such as stone content, soil depth or color. By crowdsourcing this information over thousands of locations, the uncertainty in current soil datasets could be radically reduced, particularly in areas currently without information or where multiple interpretations are possible from different existing soil maps. Improved information on soils could benefit many research fields and applications. Better soil data could enhance assessments of soil ecosystem services (e.g. soil carbon storage) and facilitate improved process-based ecosystem modeling from local to global scales. Geo-Wiki is a crowdsourcing tool that was developed at IIASA for land cover validation using satellite imagery. Several branches are now available focused on specific aspects of land cover validation, e.g. validating cropland extent or urbanized areas. Geo-Wiki Pictures is a smart phone application for collecting land cover related information on the ground. The extension of Geo-Wiki to a mobile environment provides a tool for experts in land cover validation but is also a way of reaching the general public in the validation of land cover. Here we propose a Soil Geo-Wiki tool that builds on the existing functionality of the Geo-Wiki application, which will be largely designed for the collection and sharing of soil information. Two distinct applications are envisaged: an expert-oriented application mainly for scientific purposes, which will use soil science related language (e.g. WRB or any other global reference soil classification system) and allow experts to upload and share scientifically rigorous soil data; and an application oriented towards the general public, which will be more focused on describing well observed, individual soil properties using simplified classification keys. The latter application will avoid the use of soil science related terminology and focus on the most useful soil parameters such as soil surface features, stone content, soil texture, soil plasticity, calcium carbonate presence, soil color, soil pH, soil repellency, and soil depth. Collection of soil and landscape pictures will also be supported in Soil Geo-Wiki to allow for comprehensive data collection while simultaneously allowing for quality checking by experts.

Ground truth management system to support multispectral scanner /MSS/ digital analysis

NASA Technical Reports Server (NTRS)

Coiner, J. C.; Ungar, S. G.

1977-01-01

A computerized geographic information system for management of ground truth has been designed and implemented to relate MSS classification results to in situ observations. The ground truth system transforms, generalizes and rectifies ground observations to conform to the pixel size and shape of high resolution MSS aircraft data. These observations can then be aggregated for comparison to lower resolution sensor data. Construction of a digital ground truth array allows direct pixel by pixel comparison between classification results of MSS data and ground truth. By making comparisons, analysts can identify spatial distribution of error within the MSS data as well as usual figures of merit for the classifications. Use of the ground truth system permits investigators to compare a variety of environmental or anthropogenic data, such as soil color or tillage patterns, with classification results and allows direct inclusion of such data into classification operations. To illustrate the system, examples from classification of simulated Thematic Mapper data for agricultural test sites in North Dakota and Kansas are provided.

Geological Engineering Characteristics of the Residual Soil: Implementation for Soil Bearing Capacity at Gayungan, Surabaya, East Java

NASA Astrophysics Data System (ADS)

Rukmana, Y. Y.; Ridwan, M.

2018-01-01

This paper presents the results of soil investigation on the residual soil at Gayungan Surabaya. The methodology of the research consists of Drilling + Standard Penetration Test (ASTM D1586-99), sampling and laboratory test for index properties & mechanical of soil, then analyzed for Soil Bearing Capacity (Meyerhoff, 1976). Field test analysis data showed that Bore Hole.01(BH.01) and Bore Hole.03 (BH.03) were dominated by Sand / Sandy clay layer with Standart Penetration Test (SPT) values: 6-68, whereas in BH.02 was dominated by Clayey sand layer with Standard Penetration Test (SPT) values: 32-68. Based on Soil classification according to Unified Soil Classification System (USCS), the soil type at the research area consisted of ML (Silt with Low plasticity), CL ( Clay with low plasticity), MH (Silt with High plasticity), and SP (Sand with Poor gradation). Based on the borlog data and soil bearing capacity analysis of the research area is recommended: for The Deep foundation to reaches at least 16 meters depth with Qa = 1160.40-2032.80 kN / m2, and Shallow foundation reaches at least 1-2 meters deep with Qa = 718.25 kN / M2.

Soil Classification and Treatment.

ERIC Educational Resources Information Center

Clemson Univ., SC. Vocational Education Media Center.

This instructional unit was designed to enable students, primarily at the secondary level, to (1) classify soils according to current capability classifications of the Soil Conservation Service, (2) select treatments needed for a given soil class according to current recommendations provided by the Soil Conservation Service, and (3) interpret a…

Classification and evaluation for forest sites on the Northern Cumberland Plateau

Treesearch

Glendon W. Smalley

1986-01-01

Presents a comprehensive forest site classifictation system for the North Cumberland Plateau in north-central Tennessee and eastern Kentucky. The system is based on physiograhpy, geology, soils, topography, and vegetation.

Plant community classification for alpine vegetation on the Beaverhead National Forest, Montana

Treesearch

Stephen V. Cooper; Peter Lesica; Deborah Page-Dumroese

1997-01-01

Vegetation of the alpine zone of eight mountain ranges in southwestern Montana was classified using IWINSPAN, DECORAN, and STRATA-algorithms embedded within the U.S. Forest Service Northern Region's ECADS (ecological classification and description system) program. Quantitative estimates of vegetation and soil attributes were sampled from 138 plots. Vegetation...

Soil geomorphic classification, soil taxonomy, and effects on soil richness assessments

Treesearch

Jonathan D. Phillips; Daniel A. Marion

2007-01-01

The study of pedodiversity and soil richness depends on the notion of soils as discrete entities. Soil classifications are often criticized in this regard because they depend in part on arbitrary or subjective criteria. In this study soils were categorized on the basis of the presence or absence of six lithological and morphological characteristics. Richness vs. area...

Classification of Effective Soil Depth by Using Multinomial Logistic Regression Analysis

NASA Astrophysics Data System (ADS)

Chang, C. H.; Chan, H. C.; Chen, B. A.

2016-12-01

Classification of effective soil depth is a task of determining the slopeland utilizable limitation in Taiwan. The "Slopeland Conservation and Utilization Act" categorizes the slopeland into agriculture and husbandry land, land suitable for forestry and land for enhanced conservation according to the factors including average slope, effective soil depth, soil erosion and parental rock. However, sit investigation of the effective soil depth requires a cost-effective field work. This research aimed to classify the effective soil depth by using multinomial logistic regression with the environmental factors. The Wen-Shui Watershed located at the central Taiwan was selected as the study areas. The analysis of multinomial logistic regression is performed by the assistance of a Geographic Information Systems (GIS). The effective soil depth was categorized into four levels including deeper, deep, shallow and shallower. The environmental factors of slope, aspect, digital elevation model (DEM), curvature and normalized difference vegetation index (NDVI) were selected for classifying the soil depth. An Error Matrix was then used to assess the model accuracy. The results showed an overall accuracy of 75%. At the end, a map of effective soil depth was produced to help planners and decision makers in determining the slopeland utilizable limitation in the study areas.

A study of the effectiveness of the use of gypsum and volcanic ash against the stability of clay soil in terms of UCT and CBR values

NASA Astrophysics Data System (ADS)

Roesyanto; Iskandar, R.; Hastuty, IP; Lubis, AIU

2018-02-01

Soil stabilization is an effort to improve engineering properties of soil. The conventional soil stabilization is by adding additives to the soil such as Portland cement, lime, and bitumen. The clay stabilization research was done by adding gypsum and volcanic ash. The research purposes were to find out the value of engineering properties of clay due to the addition of 2% gypsum and 2% - 15% volcanic ash. The soil was classified as Clay - Low Plasticity (CL) based on USCS and was classified as A-7-6 (10) based on AASHTO classification system. The UCT values of original soil and original soil plus 2% gypsum were 1.40 kg/cm2 and 1.66 kg/cm2 respectively. The CBR soaked and unsoaked values of original soil were 4.44% and 6.28% correspondingly. Meanwhile, CBR soaked and CBR unsoaked values of original soil plus 2% gypsum were 6.74% and 8.02% respectively. The research results showed that the additives materials of gypsum and volcanic ash improved the engineering properties of clay. The UCT result from the stabilized soil by 2% gypsum and 10% volcanic ash gave value of 2.79 kg/cm2 (increased 99.28% from original soil). For CBR test, the most effective mixture were in variation of 2% gypsum and 9% volcanic ash which gave value of 9.07% (104.27% increase from original soil) for CBR soaked and 10.29% (63.85% increase from original soil) for CBR unsoaked. The stabilized soil with 2% gypsum and 9% volcanic ash was classified as CL based on USCS and was classified as A-6 (4) based on AASHTO classification system.

Classification, Properties, and Management of Aridisols.

ERIC Educational Resources Information Center

Mack, C. B.; And Others

1990-01-01

Described is a slide set which is designed to illustrate the entire range of soils found in the arid regions of the earth's surface. Information on physical and chemical soil properties, soil classification, and related soil management considerations for agricultural development are included. (CW)

Evaluation of automated global mapping of Reference Soil Groups of WRB2015

NASA Astrophysics Data System (ADS)

Mantel, Stephan; Caspari, Thomas; Kempen, Bas; Schad, Peter; Eberhardt, Einar; Ruiperez Gonzalez, Maria

2017-04-01

SoilGrids is an automated system that provides global predictions for standard numeric soil properties at seven standard depths down to 200 cm, currently at spatial resolutions of 1km and 250m. In addition, the system provides predictions of depth to bedrock and distribution of soil classes based on WRB and USDA Soil Taxonomy (ST). In SoilGrids250m(1), soil classes (WRB, version 2006) consist of the RSG and the first prefix qualifier, whereas in SoilGrids1km(2), the soil class was assessed at RSG level. Automated mapping of World Reference Base (WRB) Reference Soil Groups (RSGs) at a global level has great advantages. Maps can be updated in a short time span with relatively little effort when new data become available. To translate soil names of older versions of FAO/WRB and national classification systems of the source data into names according to WRB 2006, correlation tables are used in SoilGrids. Soil properties and classes are predicted independently from each other. This means that the combinations of soil properties for the same cells or soil property-soil class combinations do not necessarily yield logical combinations when the map layers are studied jointly. The model prediction procedure is robust and probably has a low source of error in the prediction of RSGs. It seems that the quality of the original soil classification in the data and the use of correlation tables are the largest sources of error in mapping the RSG distribution patterns. Predicted patterns of dominant RSGs were evaluated in selected areas and sources of error were identified. Suggestions are made for improvement of WRB2015 RSG distribution predictions in SoilGrids. Keywords: Automated global mapping; World Reference Base for Soil Resources; Data evaluation; Data quality assurance References 1 Hengl T, de Jesus JM, Heuvelink GBM, Ruiperez Gonzalez M, Kilibarda M, et al. (2016) SoilGrids250m: global gridded soil information based on Machine Learning. Earth System Science Data (ESSD), in review. 2 Hengl T, de Jesus JM, MacMillan RA, Batjes NH, Heuvelink GBM, et al. (2014) SoilGrids1km — Global Soil Information Based on Automated Mapping. PLoS ONE 9(8): e105992. doi:10.1371/journal.pone.0105992

Using Landsat MSS data with soils information to identify wetland habitats

NASA Technical Reports Server (NTRS)

Ernst, C. L.; Hoffer, R. M.

1981-01-01

A previous study showed that certain fresh water wetland vegetation types can be spectrally separated when a maximum likelihood classification procedure is applied to Landsat spectral data. However, wetland and upland types which have similar vegetative life forms (e.g., upland hardwoods and hardwood swamps) are often confused because of spectral similarity. Therefore, the current investigation attempts to differentiate similar wetland and upland types by combining Landsat multispectral scanner (MSS) data with soils information. The Pigeon River area in northern Indiana used in the earlier study was also employed in this investigation. A layered classification algorithm which combined soils and spectral data was used to generate a wetland classification. The results of the spectral/soils wetland classification are compared to the previous classification that had been based on spectral data alone. The results indicate wetland habitat mapping can be improved by combining soils and other ancillary data with Landsat spectral data.

Ecological classification and management characteristics of montane forest land in southwestern Washington.

Treesearch

D.G. Brockway; C. Topik

1984-01-01

Vegetation, soil, and site data werecollectedthroughout the forested portion of the Pacific silver fir and mountain hemlock zones of the Gifford Pinchot National Forest as part of the Forest Service program to develop anecoIogicallybasedplant association classification system for the Pacific Northwest Region. The major objective of sampling was to include a wide...

Bolivian satellite technology program on ERTS natural resources

NASA Technical Reports Server (NTRS)

Brockmann, H. C. (Principal Investigator); Bartoluccic C., L.; Hoffer, R. M.; Levandowski, D. W.; Ugarte, I.; Valenzuela, R. R.; Urena E., M.; Oros, R.

1977-01-01

The author has identified the following significant results. Application of digital classification for mapping land use permitted the separation of units at more specific levels in less time. A correct classification of data in the computer has a positive effect on the accuracy of the final products. Land use unit comparison with types of soils as represented by the colors of the coded map showed a class relation. Soil types in relation to land cover and land use demonstrated that vegetation was a positive factor in soils classification. Groupings of image resolution elements (pixels) permit studies of land use at different levels, thereby forming parameters for the classification of soils.

Soil mapping and process modeling for sustainable land use management: a brief historical review

NASA Astrophysics Data System (ADS)

Brevik, Eric C.; Pereira, Paulo; Muñoz-Rojas, Miriam; Miller, Bradley A.; Cerdà, Artemi; Parras-Alcántara, Luis; Lozano-García, Beatriz

2017-04-01

Basic soil management goes back to the earliest days of agricultural practices, approximately 9,000 BCE. Through time humans developed soil management techniques of ever increasing complexity, including plows, contour tillage, terracing, and irrigation. Spatial soil patterns were being recognized as early as 3,000 BCE, but the first soil maps didn't appear until the 1700s and the first soil models finally arrived in the 1880s (Brevik et al., in press). The beginning of the 20th century saw an increase in standardization in many soil science methods and wide-spread soil mapping in many parts of the world, particularly in developed countries. However, the classification systems used, mapping scale, and national coverage varied considerably from country to country. Major advances were made in pedologic modeling starting in the 1940s, and in erosion modeling starting in the 1950s. In the 1970s and 1980s advances in computing power, remote and proximal sensing, geographic information systems (GIS), global positioning systems (GPS), and statistics and spatial statistics among other numerical techniques significantly enhanced our ability to map and model soils (Brevik et al., 2016). These types of advances positioned soil science to make meaningful contributions to sustainable land use management as we moved into the 21st century. References Brevik, E., Pereira, P., Muñoz-Rojas, M., Miller, B., Cerda, A., Parras-Alcantara, L., Lozano-Garcia, B. Historical perspectives on soil mapping and process modelling for sustainable land use management. In: Pereira, P., Brevik, E., Muñoz-Rojas, M., Miller, B. (eds) Soil mapping and process modelling for sustainable land use management (In press). Brevik, E., Calzolari, C., Miller, B., Pereira, P., Kabala, C., Baumgarten, A., Jordán, A. 2016. Historical perspectives and future needs in soil mapping, classification and pedological modelling, Geoderma, 264, Part B, 256-274.

Uncertainties and Solutions Related to Use of WRB (2007) in the Boreo-nemoral zone, Case of Latvia

NASA Astrophysics Data System (ADS)

Kasparinskis, Raimonds; Nikodemus, Olgerts; Rolavs, Nauris

2014-05-01

Relatively high diversity of soils groups according to the WRB (2007) classification is observed in forest ecosystems in the boreo-nemoral zone in Latvia. This is due to the geological genesis of area and environmental conditions (Kasparinskis, Nikodemus, 2012), as well as historical land use and management (Nikodemus et al., 2013). Due to the relatively young soils, Albic, Spodic and Cambic horizons are relatively weakly expressed in many cases. Relatively well developed Albic horizons occur in sandy forest soils, but unusually well expressed Spodic features are observed. In some cases there is a Cambic horizon, however location of Cambisols in the WRB (2007) soil classification sequence does not provide an opportunity to classify these soils as Cambisols, but they are classified as Arenosols. This sequence does not reflect the logical sheme of soil development, and therefore raises the question about location of Podzols, Arenosols and Cambisols in the sequence of WRB (2007) soil classification. Soils with two parent materials (abrupt textural change) are relatively common in Latvia, where conceptually on the small scale mapping results in classification as the soil group Planosols, but in many cases there is occurrence of Fluvic materials, as parent material in the upper part of the soil profile is formed by Baltic Ice lake sandy sediments - this leads to question about the location of Fluvisols and Planosols in the sequence of the WRB (2007) soil classification. Soil research has found cases, where a relatively well developed Spodic horizon was established as the result of ground water table depth in areas of abrupt textural change. In this case the profile corresponds to the soil group of Podzols, however in some cases - Gleysols not Planosols due to a high ground water table. Therefore there is a need for discussion also about the location of Podzols and Planosols in the sequence of the WRB (2007) soil classification. The above mentioned questions raise problems related to unambiguous determination of soil groups. Soil classification must be very precise by reflecting relationships of soil forming processes. In the development of international soil classification it is advisable to pay more attention on ecological processes. This study was supported by the European Social Fund No. 2013/0020/1DP/1.1.1.2.0/13/APIA/VIAA/066. References: IUSS Working Group, 2007. World Reference Base for Soil Resources 2006, first update 2007. World Soil Resources Reports 103. FAO, Rome. 103-116. Kasparinskis R., Nikodemus O. 2012. Influence of environmental factors on the spatial distribution and diversity of forest soil in Latvia. Estonian Journal of Earth Sciences. 61(1): 48-64. Nikodemus O., Kasparinskis R., Kukuls I. 2013. Influence of Afforestation on Soil Genesis, Morphology and Properties in Glacial Till Deposits. Archives of Agronomy and Soil Science. 59(3): 449-465.

Land classification of the standing stone state forest and state park on the eastern highland rim in Tennessee: the interaction of geology, topography, and soils

Treesearch

Glendon W. Smalley; Carlie McCowan; S. David Todd; Phillip M. Morrissey; J. Andrew McBride

2013-01-01

This paper summarizes the application of a land classification system developed by the senior author to the Standing Stone State Forest and State Park (SSSF&SP) on the Eastern Highland Rim. Landtypes are the most detailed level in the hierarchical system and represent distinct units of the landscape (mapped at a scale of 1:24,000) as defined by climate, geology,...

Radar remote sensing for crop classification and canopy condition assessment: Ground-data documentation

NASA Technical Reports Server (NTRS)

Ulaby, F. T. (Principal Investigator); Jung, B.; Gillespie, K.; Hemmat, M.; Aslam, A.; Brunfeldt, D.; Dobson, M. C.

1983-01-01

A vegetation and soil-moisture experiment was conducted in order to examine the microwave emission and backscattering from vegetation canopies and soils. The data-acquisition methodology used in conjunction with the mobile radar scatterometer (MRS) systems is described and associated ground-truth data are documented. Test fields were located in the Kansas River floodplain north of Lawrence, Kansas. Ten fields each of wheat, corn, and soybeans were monitored over the greater part of their growing seasons. The tabulated data summarize measurements made by the sensor systems and represent target characteristics. Target parameters describing the vegetation and soil characteristics include plant moisture, density, height, and growth stage, as well as soil moisture and soil-bulk density. Complete listings of pertinent crop-canopy and soil measurements are given.

Soils of northern spurs of the Cherskii Ridge in the area of the northern pole of cold: Morphology, properties, and classification

NASA Astrophysics Data System (ADS)

Okoneshnikova, M. V.; Desyatkin, R. V.

2017-08-01

The soils in the area of the northern pole of cold located on the interfluve between the Yana and Adycha rivers within the spurs of Kisilyakh Ridge included in the mountain system of Cherskii Ridge have been studied for the first time. The profile-genetic approach has been applied to describe the soils and determine their classification position. It is found that the major soil types in this region are the soils of the postlithogenic trunk belonging to the orders of lithozems (Cryic Leptosols), gley soils (Gleyic Skeletic Cryosols), and Al-Fe-humus soils (Spodic Skeletic Cryosols). The ecological ranges of altitudinal zones— the taiga zone with various types of lithozems below 630-700 m a.s.l. and the tundra zone with combinations of gley and nongley cryogenic soils above these heights—have been established. The development of gley or nongley soils is specified by the local orogenic and lithological conditions and slope aspect, which, in turn, control the degree of drainage and the presence and character of permafrost. In the profile of mountainous gley soils (gleyzems) with shallow ice-rich permafrost, cryogenic processes and features typical of the analogues of these soils on plains—cryogenic cracking, cryoturbation, solifluction, thixotropy, oxiaquic features above permafrost, saturation of the soil profile with mobile humus, etc.—are typical.

From landscape to domain: Soils role in landscape classifications

USDA-ARS?s Scientific Manuscript database

Soil landscape classifications are designed to divide landscapes into units with significance for the provisioning and regulating of ecosystem services and the development of conservation plans for natural resources. More specifically, such classifications serve as the basis for stratifying manageme...

24 CFR 3285.4 - Incorporation by reference (IBR).

Code of Federal Regulations, 2010 CFR

2010-04-01

... purchase from the Structural Engineering Institute/American Society of Civil Engineers (SEI/ASCE), 1801... for Engineering Purposes (Unified Soil Classification System), 2000, IBR approved for the table at...

Binational digital soils map of the Ambos Nogales watershed, southern Arizona and northern Sonora, Mexico

USGS Publications Warehouse

Norman, Laura

2004-01-01

We have prepared a digital map of soil parameters for the international Ambos Nogales watershed to use as input for selected soils-erosion models. The Ambos Nogales watershed in southern Arizona and northern Sonora, Mexico, contains the Nogales wash, a tributary of the Upper Santa Cruz River. The watershed covers an area of 235 km2, just under half of which is in Mexico. Preliminary investigations of potential erosion revealed a discrepancy in soils data and mapping across the United States-Mexican border due to issues including different mapping resolutions, incompatible formatting, and varying nomenclature and classification systems. To prepare a digital soils map appropriate for input to a soils-erosion model, the historical analog soils maps for Nogales, Ariz., were scanned and merged with the larger-scale digital soils data available for Nogales, Sonora, Mexico using a geographic information system.

Classification problems of Mount Kenya soils

NASA Astrophysics Data System (ADS)

Mutuma, Evans; Csorba, Ádám; Wawire, Amos; Dobos, Endre; Michéli, Erika

2017-04-01

Soil sampling on the agricultural lands covering 1200 square kilometers in the Eastern part of Mount Kenya was carried out to assess the status of soil organic carbon (SOC) as a soil fertility indicator, and to create an up-to-date soil classification map. The geology of the area consists of volcanic rocks and recent superficial deposits. The volcanic rocks are related to the Pliocene time; mainly: lahars, phonolites, tuffs, basalt and ashes. A total of 28 open profiles and 49 augered profiles with 269 samples were collected. The samples were analyzed for total carbon, organic carbon, particle size distribution, percent bases, cation exchange capacity and pH among other parameters. The objective of the study was to evaluate the variability of SOC in different Reference Soil Groups (RGS) and to compare the determined classification units with the KENSOTER database. Soil classification was performed based on the World Reference Base (WRB) for Soil Resources 2014. Based on the earlier surveys, geological and environmental setting, Nitisols were expected to be the dominant soils of the sampled area. However, this was not the case. The major differences to earlier survey data (KENSOTER database) are the presence of high activity clays (CEC value range 27.6 cmol/kg - 70 cmol/kg), high silt content (range 32.6 % - 52.4 %) and silt/clay ratio (range of 0.6 - 1.4) keeping these soils out of the Nitisols RSG. There was good accordance in the morphological features with the earlier survey but failed the silt/clay ratio criteria for Nitisols. This observation calls attention to set new classification criteria for Nitisols and other soils of warm, humid regions with variable rate of weathering to avoid difficulties in interpretation. To address the classification problem, this paper further discusses the taxonomic relationships between the studied soils. On the contrary most of the diagnostic elements (like the presence Umbric horizon, Vitric and Andic properties) and the some qualifiers (Humic, Dystric, Clayic, Skeletic, Leptic, etc) represent useful information for land use and management in the area.

Hydrogeomorphic Classification of Wetlands on Mt. Desert Island, Maine, Including Hydrologic Susceptibility Factors for Wetlands in Acadia National Park

USGS Publications Warehouse

Nielsen, Martha G.

2006-01-01

The U.S. Geological Survey, in cooperation with the National Park Service, developed a hydrogeomorphic (HGM) classification system for wetlands greater than 0.4 hectares (ha) on Mt. Desert Island, Maine, and applied this classification using map-scale data to more than 1,200 mapped wetland units on the island. In addition, two hydrologic susceptibility factors were defined for a subset of these wetlands, using 11 variables derived from landscape-scale characteristics of the catchment areas of these wetlands. The hydrologic susceptibility factors, one related to the potential hydrologic pathways for contaminants and the other to the susceptibility of wetlands to disruptions in water supply from projected future changes in climate, were used to indicate which wetlands (greater than 1 ha) in Acadia National Park (ANP) may warrant further investigation or monitoring. The HGM classification system consists of 13 categories: Riverine-Upper Perennial, Riverine-Nonperennial, Riverine- Tidal, Depressional-Closed, Depressional-Semiclosed, Depressional-Open, Depressional-No Ground-Water Input, Mineral Soil Flat, Organic Soil Flat, Tidal Fringe, Lacustrine Fringe, Slope, and Hilltop/Upper Hillslope. A dichotomous key was developed to aid in the classification of wetlands. The National Wetland Inventory maps produced by the U.S. Fish and Wildlife Service provided the wetland mapping units used for this classification. On the basis of topographic map information and geographic information system (GIS) layers at a scale of 1:24,000 or larger, 1,202 wetland units were assigned a preliminary HGM classification. Two of the 13 HGM classes (Riverine-Tidal and Depressional-No Ground-Water Input) were not assigned to any wetlands because criteria for determining those classes are not available at that map scale, and must be determined by more site-specific information. Of the 1,202 wetland polygons classified, which cover 1,830 ha in ANP, 327 were classified as Slope, 258 were Depressional (Open, Semiclosed, and Closed), 231 were Riverine (Upper Perennial and Nonperennial), 210 were Soil Flat (Mineral and Organic), 68 were Lacustrine Fringe, 51 were Tidal Fringe, 22 were Hilltop/Upper Hillslope, and another 35 were small open water bodies. Most small, isolated wetlands classified on the island are Slope wetlands. The least common, Hilltop/Upper Hillslope wetlands, only occur on a few hilltops and shoulders of hills and mountains. Large wetland complexes generally consist of groups of Depressional wetlands and Mineral Soil Flat or Organic Soil Flat wetlands, often with fringing Slope wetlands at their edges and Riverine wetlands near streams flowing through them. The two analyses of wetland hydrologic susceptibility on Mt. Desert Island were applied to 186 wetlands located partially or entirely within ANP. These analyses were conducted using individually mapped catchments for each wetland. The 186 wetlands were aggregated from the original 1,202 mapped wetland polygons on the basis of their HGM classes. Landscape-level hydrologic, geomorphic, and soil variables were defined for the catchments of the wetlands, and transformed into scaled scores from 0 to 10 for each variable. The variables included area of the wetland, area of the catchment, area of the wetland divided by the area of the catchment, the average topographic slope of the catchment, the amount of the catchment where bedrock crops out with no soil cover or excessively thin soil cover, the amount of storage (in lakes and wetlands) in the catchment, the topographic relief of the catchment, the amount of clay-rich soil in the catchment, the amount of manmade impervious surface, whether the wetland had a stream inflow, and whether the wetland had a hydraulic connection to a lake or estuary. These data were determined using a GIS and data layers mapped at a scale of 1:24,000 or larger. These landscape variables were combined in different ways for the two hydrologic susceptibility fact

Fines classification based on sensitivity to pore-fluid chemistry

USGS Publications Warehouse

Jang, Junbong; Santamarina, J. Carlos

2016-01-01

The 75-μm particle size is used to discriminate between fine and coarse grains. Further analysis of fine grains is typically based on the plasticity chart. Whereas pore-fluid-chemistry-dependent soil response is a salient and distinguishing characteristic of fine grains, pore-fluid chemistry is not addressed in current classification systems. Liquid limits obtained with electrically contrasting pore fluids (deionized water, 2-M NaCl brine, and kerosene) are combined to define the soil “electrical sensitivity.” Liquid limit and electrical sensitivity can be effectively used to classify fine grains according to their fluid-soil response into no-, low-, intermediate-, or high-plasticity fine grains of low, intermediate, or high electrical sensitivity. The proposed methodology benefits from the accumulated experience with liquid limit in the field and addresses the needs of a broader range of geotechnical engineering problems.

Integrated Universal Soil Loss Equation (USLE) and Geographical Information System (GIS) for Soil Erosion Measurement in basin of Asap river, Central Vietnam

NASA Astrophysics Data System (ADS)

Pham Gia, Tung; Degener, Jan; Kappas, Martin

2017-04-01

The study was conducted in Asap river basin, A Luoi district, Thua Thien Hue Province, Vietnam, using the Universal Soil Loss Equation (USLE) and Geographical Information System (GIS) to determine the soil erosion status. The results show strong effect of the heavy rainfall and high slope on the erosion level in the research area. More than 40% of land area lost over 10 tons/ha/year. The natural forest land lost the most by averagely is 38.4 tons/ha/year, while the agricultural land showed less with 2.79 tons for paddy rice land use type and 7.58 tons for upland crops yearly. Comparison between some places of Vietnam and the Southeast Asia showed that soil erosion in watersheds of Asap is more serious. We have been proposed a recommendation on changing the classification system of land use type in Vietnam for more accurate in soil erosion measurement. Keywords: Land use type, Soil erosion, USLE, Central Vietnam.

Toward Soil Spatial Information Systems (SSIS) for global modeling and ecosystem management

NASA Technical Reports Server (NTRS)

Baumgardner, Marion F.

1995-01-01

The general objective is to conduct research to contribute toward the realization of a world soils and terrain (SOTER) database, which can stand alone or be incorporated into a more complete and comprehensive natural resources digital information system. The following specific objectives are focussed on: (1) to conduct research related to (a) translation and correlation of different soil classification systems to the SOTER database legend and (b) the inferfacing of disparate data sets in support of the SOTER Project; (2) to examine the potential use of AVHRR (Advanced Very High Resolution Radiometer) data for delineating meaningful soils and terrain boundaries for small scale soil survey (range of scale: 1:250,000 to 1:1,000,000) and terrestrial ecosystem assessment and monitoring; and (3) to determine the potential use of high dimensional spectral data (220 reflectance bands with 10 m spatial resolution) for delineating meaningful soils boundaries and conditions for the purpose of detailed soil survey and land management.

Landscape variation in species diversity and succession as related to topography, soils and human disturbance

Treesearch

Jeffery N. Pearcy; David M. Hix; Stacy A. Drury

1995-01-01

Three hundred and thirty-two plots have been sampled on the Wayne National Forest of southeastern Ohio, for the purpose of developing an ecological classification system (ECS). The ECS will be based on the herbaceous and woody vegetation, soils and topography of mature (80-140 year-old), relatively-undisturbed forests. Species diversity changes little across this...

Study on a pattern classification method of soil quality based on simplified learning sample dataset

USGS Publications Warehouse

Zhang, Jiahua; Liu, S.; Hu, Y.; Tian, Y.

2011-01-01

Based on the massive soil information in current soil quality grade evaluation, this paper constructed an intelligent classification approach of soil quality grade depending on classical sampling techniques and disordered multiclassification Logistic regression model. As a case study to determine the learning sample capacity under certain confidence level and estimation accuracy, and use c-means algorithm to automatically extract the simplified learning sample dataset from the cultivated soil quality grade evaluation database for the study area, Long chuan county in Guangdong province, a disordered Logistic classifier model was then built and the calculation analysis steps of soil quality grade intelligent classification were given. The result indicated that the soil quality grade can be effectively learned and predicted by the extracted simplified dataset through this method, which changed the traditional method for soil quality grade evaluation. ?? 2011 IEEE.

Geotechnical soil characterization of intact Quaternary deposits forming the March 22, 2014 SR-530 (Oso) landslide, Snohomish County, Washington

USGS Publications Warehouse

Riemer, Michael F.; Collins, Brian D.; Badger, Thomas C.; Toth, Csilla; Yu, Yat Chun

2015-01-01

This report provides a description of the methods used to obtain and test the intact soil stratigraphy behind the headscarp of the March 22 landslide. Detailed geotechnical index testing results are presented for 24 soil samples representing the stratigraphy at 19 different depths along a 650 ft (198 m) soil profile. The results include (1) the soil's in situ water content and unit weight (where applicable); (2) specific gravity of soil solids; and (3) each sample's grain-size distribution, critical limits for fine-grain water content states (that is, the Atterberg limits), and official Unified Soil Classification System (USCS) designation. In addition, preliminary stratigraphy and geotechnical relations within and between soil units are presented.

A Brief History of Soil Mapping and Classification in the USA

NASA Astrophysics Data System (ADS)

Brevik, Eric C.; Hartemink, Alfred E.

2014-05-01

Soil maps show the distribution of soils across an area but also depict soil science theory and ideas on soil formation and classification at the time the maps were created. The national soil mapping program in the USA was established in 1899. The first nation-wide soil map was published by M. Whitney in 1909 and showed soil provinces that were largely based on geology. In 1912, G.N. Coffey published the first country-wide map based on soil properties. The map showed 5 broad soil units that used parent material, color and drainage as diagnostic criteria. The 1913 national map was produced by C.F. Marbut, H.H. Bennett, J.E. Lapham, and M.H. Lapham and showed broad physiographic units that were further subdivided into soil series, soil classes and soil types. In 1935, Marbut drafted a series of maps based on soil properties, but these maps were replaced as official U.S. soil maps in 1938 with the work of M. Baldwin, C.E. Kellogg, and J. Thorp. A series of soil maps similar to modern USA maps appeared in the 1960s with the 7th Approximation followed by revisions with the 1975 and 1999 editions of Soil Taxonomy. This review has shown that soil maps in the United States produced since the early 1900s moved initially from a geologic-based concept to a pedologic concept of soils. Later changes were from property-based systems to process-based, and then back to property-based. The information in this presentation is based on Brevik and Hartemink (2013). Brevik, E.C., and A.E. Hartemink. 2013. Soil Maps of the United States of America. Soil Science Society of America Journal 77:1117-1132. doi:10.2136/sssaj2012.0390.

Estonian soil classification as a tool for recording information on soil cover and its matching with local site types, plant covers and humus forms classifications

NASA Astrophysics Data System (ADS)

Kõlli, Raimo; Tõnutare, Tõnu; Rannik, Kaire; Krebstein, Kadri

2015-04-01

Estonian soil classification (ESC) has been used successfully during more than half of century in soil survey, teaching of soil science, generalization of soil databases, arrangement of soils sustainable management and others. The Estonian normally developed (postlithogenic) mineral soils (form 72.4% from total area) are characterized by mean of genetic-functional schema, where the pedo-ecological position of soils (ie. location among other soils) is given by means of three scalars: (i) 8 stage lithic-genetic scalar (from rendzina to podzols) separates soils each from other by parent material, lithic properties, calcareousness, character of soil processes and others, (ii) 6 stage moisture and aeration conditions scalar (from aridic or well aerated to permanently wet or reductic conditions), and (iii) 2-3 stage soil development scalar, which characterizes the intensity of soil forming processes (accumulation of humus, podzolization). The organic soils pedo-ecological schema, which links with histic postlithogenic soils, is elaborated for characterizing of peatlands superficial mantle (form 23.7% from whole soil cover). The position each peat soil species among others on this organic (peat) soil matrix schema is determined by mean of 3 scalars: (i) peat thickness, (ii) type of paludification or peat forming peculiarities, and (iii) stage of peat decomposition or peat type. On the matrix of abnormally developed (synlithogenic) soils (all together 3.9%) the soil species are positioned (i) by proceeding in actual time geological processes as erosion, fluvial processes (at vicinity of rivers, lakes or sea) or transforming by anthropogenic and technological processes, and (ii) by 7 stage moisture conditions (from aridic to subaqual) of soils. The most important functions of soil cover are: (i) being a suitable environment for plant productivity; (ii) forming adequate conditions for decomposition, transformation and conversion of falling litter (characterized by humus cover type); (iii) being compartment for deposition of humus, individual organic compounds, plant nutrition elements, air and water, and (iv) forming (bio)chemically variegated active space for soil type specific edaphon. For studying of ESC matching with others ecosystem compartments classifications the comparative analysis of corresponding classification schemas was done. It may be concluded that forest and natural grasslands site types as well the plant associations of forests and grasslands correlate (match) well with ESC and therefore these compartments may be adequately expressed on soil cover matrixes. Special interest merits humus cover (in many countries known as humus form), which is by the issue natural body between plant and soil or plant cover and soil cover. The humus cover, which lied on superficial part of soil cover, has been formed by functional interrelationships of plants and soils, reflects very well the local pedo-ecological conditions (both productivity and decomposition cycles) and, therefore, the humus cover types are good indicators for characterizing of local pedo-ecological conditions. The classification of humus covers (humus forms) should be bound with soil classifications. It is important to develop a pedocentric approach in treating of fabric and functioning of natural and agro-ecosystems. Such, based on soil properties, ecosystem approach to management and protection natural resources is highly recommended at least in temperate climatic regions. The sound matching of soil and plant cover is of decisive importance for sustainable functioning of ecosystem and in attaining a good environmental status of the area.

Synoptic typing: interdisciplinary application methods with three practical hydroclimatological examples

NASA Astrophysics Data System (ADS)

Siegert, C. M.; Leathers, D. J.; Levia, D. F.

2017-05-01

Synoptic classification is a methodology that represents diverse atmospheric variables and allows researchers to relate large-scale atmospheric circulation patterns to regional- and small-scale terrestrial processes. Synoptic classification has often been applied to questions concerning the surface environment. However, full applicability has been under-utilized to date, especially in disciplines such as hydroclimatology, which are intimately linked to atmospheric inputs. This paper aims to (1) outline the development of a daily synoptic calendar for the Mid-Atlantic (USA), (2) define seasonal synoptic patterns occurring in the region, and (3) provide hydroclimatological examples whereby the cascading response of precipitation characteristics, soil moisture, and streamflow are explained by synoptic classification. Together, achievement of these objectives serves as a guide for development and use of a synoptic calendar for hydroclimatological studies. In total 22 unique synoptic types were identified, derived from a combination of 12 types occurring in the winter (DJF), 13 in spring (MAM), 9 in summer (JJA), and 11 in autumn (SON). This includes six low pressure systems, four high pressure systems, one cold front, three north/northwest flow regimes, three south/southwest flow regimes, and five weakly defined regimes. Pairwise comparisons indicated that 84.3 % had significantly different rainfall magnitudes, 86.4 % had different rainfall durations, and 84.7 % had different rainfall intensities. The largest precipitation-producing classifications were not restricted to low pressure systems, but rather to patterns with access to moisture sources from the Atlantic Ocean and easterly (on-shore) winds, which transport moisture inland. These same classifications resulted in comparable rates of soil moisture recharge and streamflow discharge, illustrating the applicability of synoptic classification for a range of hydroclimatological research objectives.

Presenting the 3rd edition of WRB

NASA Astrophysics Data System (ADS)

Schad, Peter

2014-05-01

The third edition of the international soil classification system "World Reference Base for Soil Resources" (WRB) will be presented during der 20th World Congress of Soil Science, Jeju, Korea, June 9-12. The second edition was published in 2006 and the first in 1998, which, in turn, was based on the Legends of the FAO Soil Map of the World. Now, after eight years of experience with the second edition, time was due for a revision. The major changes are: 1. The second edition had two different qualifier sequences for naming soils (IUSS Working Group WRB, 2006, update 2007) and for creating map legends (Guidelines for creating small-scale map legends using the WRB; IUSS Working Group WRB, 2010). The third edition has one sequence for both. The qualifiers for every Reference Soil Group are subdivided into a small number of main qualifiers that are ranked and a larger number of additional qualifiers that are not ranked and given in an alphabetical order. The name of a pedon must comprise all applying qualifiers. The name of a map unit comprises a specified small number of main qualifiers, depending on scale, whereas all other qualifiers are optional. 2. For some soils, problems have been reported. Albeluvisols are difficult to detect in the field and cover only small surfaces. They have been replaced by Retisols, which have a broader definition that is easier to identify in the field. 3. The use of some diagnostics was difficult. Examples are: The argic horizon had too low limit values, so we had much more soils with argic horizons than justified. The definitions of the cambic horizon and the gleyic and stagnic properties were not precise enough. Organic material, mollic and umbric horizons had an unnecessary complicated definition. 4. Some changes in the key to the Reference Soil Groups seemed to be justified. Fluvisols were moved further down, Durisols and Gypsisols switched their position, also Arenosols and Cambisols. The soils with an argic horizon were brought into a new sequence. 5. The umbrella function of WRB aims to allow the allocation of soil classes existing in a national classification system within the WRB. Characteristics that in a national system are regarded to be important must be considered in WRB - not necessarily at the highest level, but at least somewhere. The third edition of WRB allows a better accommodation of soil types, e.g., of the Australian and the Brazilian system. 6. Some environments or even ecoregions had not been well represented in WRB. The third edition allows a better accommodation of soils of ultra-continental permafrost regions, acid-sulphate soils and Technosols. 7. How to explain complicated sets of characteristics? For the third edition, efforts were made to give better structured definitions that can be more easily grasped. The editors of the third edition are convinced that the new WRB allows a more precise classification of soils including both, a better naming of pedons and a better elaboration of soil map legends.

New Site Coefficients and Site Classification System Used in Recent Building Seismic Code Provisions

USGS Publications Warehouse

Dobry, R.; Borcherdt, R.D.; Crouse, C.B.; Idriss, I.M.; Joyner, W.B.; Martin, G.R.; Power, M.S.; Rinne, E.E.; Seed, R.B.

2000-01-01

Recent code provisions for buildings and other structures (1994 and 1997 NEHRP Provisions, 1997 UBC) have adopted new site amplification factors and a new procedure for site classification. Two amplitude-dependent site amplification factors are specified: Fa for short periods and Fv for longer periods. Previous codes included only a long period factor S and did not provide for a short period amplification factor. The new site classification system is based on definitions of five site classes in terms of a representative average shear wave velocity to a depth of 30 m (V?? s). This definition permits sites to be classified unambiguously. When the shear wave velocity is not available, other soil properties such as standard penetration resistance or undrained shear strength can be used. The new site classes denoted by letters A - E, replace site classes in previous codes denoted by S1 - S4. Site classes A and B correspond to hard rock and rock, Site Class C corresponds to soft rock and very stiff / very dense soil, and Site Classes D and E correspond to stiff soil and soft soil. A sixth site class, F, is defined for soils requiring site-specific evaluations. Both Fa and Fv are functions of the site class, and also of the level of seismic hazard on rock, defined by parameters such as Aa and Av (1994 NEHRP Provisions), Ss and S1 (1997 NEHRP Provisions) or Z (1997 UBC). The values of Fa and Fv decrease as the seismic hazard on rock increases due to soil nonlinearity. The greatest impact of the new factors Fa and Fv as compared with the old S factors occurs in areas of low-to-medium seismic hazard. This paper summarizes the new site provisions, explains the basis for them, and discusses ongoing studies of site amplification in recent earthquakes that may influence future code developments.

Analysis of SURRGO Data and Obtaining Soil Texture Classifications for Simulating Hydrologic Processes

DTIC Science & Technology

2016-07-01

Note (CHETN) describes a method using the U.S. Department of Agriculture (USDA), Natural Resources Conservation Service (NRCS), Soil Survey Geographic...the general texture classifications. 2. Another source for soil information, such as the Food and Agriculture Organization of the United Nations (FAO...science studies such as agriculture , geology, geomorphology, engineering, biology, history, etc. (Soil Survey Division Staff 1993). The procedure pulls

A discrimlnant function approach to ecological site classification in northern New England

Treesearch

James M. Fincher; Marie-Louise Smith

1994-01-01

Describes one approach to ecologically based classification of upland forest community types of the White and Green Mountain physiographic regions. The classification approach is based on an intensive statistical analysis of the relationship between the communities and soil-site factors. Discriminant functions useful in distinguishing between types based on soil-site...

Spectral band selection for classification of soil organic matter content

NASA Technical Reports Server (NTRS)

Henderson, Tracey L.; Szilagyi, Andrea; Baumgardner, Marion F.; Chen, Chih-Chien Thomas; Landgrebe, David A.

1989-01-01

This paper describes the spectral-band-selection (SBS) algorithm of Chen and Landgrebe (1987, 1988, and 1989) and uses the algorithm to classify the organic matter content in the earth's surface soil. The effectiveness of the algorithm was evaluated comparing the results of classification of the soil organic matter using SBS bands with those obtained using Landsat MSS bands and TM bands, showing that the algorithm was successful in finding important spectral bands for classification of organic matter content. Using the calculated bands, the probabilities of correct classification for climate-stratified data were found to range from 0.910 to 0.980.

CONTAINMENT TECHNOLOGIES

EPA Science Inventory

Hazardous waste containment's primary objective is to isolate wastes deemed as hazardous from man and environmental systems of air, soil, and water. Hazardous wastes differ from other waste classifications due to their increased potential to cause human health effects or environ...

Subaquatic soils in the Volga, Don and Kuban Rivers deltas.

NASA Astrophysics Data System (ADS)

Tkachenko, Anna; Gerasimova, Maria; Lychagin, Mikhail

2015-04-01

River deltas occupy a special interface position in the environment and are characterized by contrasting hydrological and landscape-geochemical regimes. Small depth of water and weak currents contribute to suspended matter deposition. Significant spread of aquatic plants provides the enrichment of subaquatic soils in organic matter. All these factors contribute to the formation of different subaquatic soils. Possibility of including them in the classification systems is discussed by many authors (Demas and Rabenhorst, 2001; Stolt et al., 2011); there is also a special subaquatic qualifier for submerged soils in WRB; however, they are still absent in many national classification systems, as well as in the recent Russian one (2008). The purpose of this research is to reveal the properties of the subaquatic soils in the Volga, Don and Kuban Rivers deltaic areas and to propose pedogenetic approaches to categorize AQUAZEMS. Investigations of deltaic areas were performed in 2010-2012 in deltaic lagoons, fresh-water bays, small channels, oxbow lakes, and also in the part of deltaic near-shore zone. Morphological descriptions of distinguishable layers (colour, texture, thickness, boundaries, consistence, plant residues and shell debris) were made in columns obtained by augering as it is done by other researchers (Stolt et al., 2011), and supplemented with analytical data (pH, Eh, TDS, particle-size composition, and Corg). It is suggested to name the horizons in aquazems in the same way as in terrestrial soils in the recent Russian soil classification system, and apply symbols starting with the combination of caps - AQ. Most typical for aquazems is their aquagley AQG horizon that has features similar to terrestrial gleys - homogeneity in color and consistence, permeation by clay, predominance of dove grey colour. The AQG horizon gradually merges into parent material - stratified bottom sediments. The "topsoil" is usually enriched in organic matter and may be different in accordance with plant communities. The highest Corg content (4-6%) was recorded under lotus (Nelumbo sp.) and reed (Phragmites australis); reed is hard to decompose and its residues preserve recognizable plant tissues. Hence, two variants of upper horizons may be identified: aquahumus horizon - AQA and aquapeat horizon - AQT. Floating plants do not create any stable horizon under active hydrodynamic processes, whereas if they are weak, a discontinuous greyish-bluish horizon, 2-3 cm thick, is formed with Сorg content not exceeding 1-2%. In active channels, mixing of the upper part of aquazem profiles by currents results in the formation of a thin yellowish-grey oxidized layer (AQOX) with a very low content of Corg: less than 1%. Following the rules of the new system of soil classification of Russia (2004, 2008) aquazems may be tentatively classified in the following way. All aquazems may be referred to the trunk of synlithogenic soils as a special aquazem order; aquazem types may be specified by the combinations of horizons, hence, typical (AQA-AQG-AQC-C), organogenic (AQT-AQG-AQC-C), and oxidized (AQA-AQOX-AQG-AQC-C). The extension of studies is sure to find new types.

Classification of wetlands and deepwater habitats of the United States

USGS Publications Warehouse

Cowardin, L.M.; Carter, V.; Golet, F.C.; LaRoe, E.T.

1985-01-01

This classification, to be used in a new inventory of wetlands and deepwater habitats of the United States, is intended to describe ecological taxa, arrange them in a system useful to resource managers, furnish units for mapping, and provide uniformity of concepts and terms. Wetlands are defined by plants (hydrophytes), soils (hydric soils), and frequency of flooding. Ecologically related areas of deep water, traditionally not considered wetlands, are included in the classification as deepwater habitats.Systems form the highest level of the classification hierarchy; five are defined-Marine, Estuarine, Riverine, Lacustrine, and Palustrine. Marine and Estuarine Systems each have two Subsystems, Subtidal and Intertidal; the Riverine System has four Subsystems, Tidal, Lower Perennial, Upper Perennial, and Intermittent; the Lacustrine has two, Littoral and Limnetic; and the Palustrine has no Subsystems.Within the Subsystems, Classes are based on substrate material and flooding regime, or on vegetative life form. The same Classes may appear under one or more of the Systems or Subsystems. Six Classes are based on substrate and flooding regime: (1) Rock Bottom with a substrate of bedrock, boulders, or stones; (2) Unconsolidated Bottom with a substrate of cobbles, gravel, sand, mud, or organic material; (3) Rocky Shore with the same substrates as Rock Bottom; (4) Unconsolidated Shore with the same substrates as Unconsolidated Bottom; (5) Streambed with any of the substrates; and (6) Reef with a substrate composed of the living and dead remains of invertebrates (corals, mollusks, or worms). The bottom Classes, (1) and (2) above, are flooded all or most of the time and the shore Classes, (3) and (4), are exposed most of the time. The Class Streambed is restricted to channels of intermittent streams and tidal channels that are dewatered at low tide. The life form of the dominant vegetation defines the five Classes based on vegetative form: (1) Aquatic Bed, dominated by plants that grow principally on or below the surface of the water; (2) Moss-Lichen Wetland, dominated by mosses or lichens; (3) Emergent Wetland, dominated by emergent herbaceous angiosperms; (4) Scrub-Shrub Wetland, dominated by shrubs or small trees; and (5) Forested Wetland, dominated by large trees.The Dominance Type, which is named for the dominant plant or animal forms, is the lowest level of the classification hierarchy. Only examples are provided for this level; Dominance Types must be developed by individual users of the classification.Modifying terms applied to the Classes or Subclasses are essential for use of the system. In tidal areas, the type and duration of flooding are described by four Water Regime Modifiers: subtidal, irregularly exposed, regularly flooded, and irregularly flooded. In nontidal areas, eight Regimes are used: permanently flooded, intermittently exposed, semipermanently flooded, seasonally flooded, saturated, temporarily flooded, intermittently flooded, and artificially flooded. A hierarchical system of Water Chemistry Modifiers, adapted from the Venice System, is used to describe the salinity of the water. Fresh waters are further divided on the basis of pH. Use of a hierarchical system of soil modifiers taken directly from U.S. soil taxonomy is also required. Special modifiers are used where appropriate: excavated, impounded, diked, partly drained, farmed, and artificial.Regional differences important to wetland ecology are described through a regionalization that combines a system developed for inland areas by R. G. Bailey in 1976 with our Marine and Estuarine provinces.The structure of the classification allows it to be used at any of several hierarchical levels. Special data required for detailed application of the system are frequently unavailable, and thus data gathering may be prerequisite to classification. Development of rules by the user will be required for specific map scales. Dominance Types and relationships of plant and anima

Classification of wetlands and deepwater habitats of the United States

USGS Publications Warehouse

Cowardin, L.M.; Carter, V.; Golet, F.C.; LaRoe, E.T.

1979-01-01

This classification, to be used in a new inventory of wetlands and deepwater habitats of the United States, is intended to describe ecological taxa, arrange them in a system useful to resource managers, furnish units for mapping, and provide uniformity of concepts and terms. Wetlands are defined by plants (hydrophytes), soils (hydric soils), and frequency of flooding. Ecologically related areas of deep water, traditionally not considered wetlands, are included in the classification as deepwater habitats.Systems form the highest level of the classification hierarchy; five are defined--Marine, Estuarine, Riverine, Lacustrine, and Palustrine. Marine and Estuarine systems each have two subsystems, Subtidal and Intertidal; the Riverine system has four subsystems, Tidal, Lower Perennial, Upper Perennial, and Intermittent; the Lacustrine has two, Littoral and Limnetic; and the Palustrine has no subsystem.Within the subsystems, classes are based on substrate material and flooding regime, or on vegetative life form. The same classes may appear under one or more of the systems or subsystems. Six classes are based on substrate and flooding regime: (1) Rock Bottom with a substrate of bedrock, boulders, or stones; (2) Unconsolidated Bottom with a substrate of cobbles, gravel, sand, mud, or organic material; (3) Rocky Shore with the same substrate as Rock Bottom; (4) Unconsolidated Shore with the same substrate as Unconsolidated Bottom; (5) Streambed with any of the substrates; and (6) Reef with a substrate composed of the living and dead remains of invertebrates (corals, mollusks, or worms). The bottom classes, (1) and (2) above, are flooded all or most of the time and the shore classes, (3) and (4), are exposed most of the time. The class Streambed is restricted to channels of intermittent streams and tidal channels that are dewatered at low tide. The life form of the dominant vegetation defines the five classes based on vegetative form: (1) Aquatic Bed, dominated by plants that grow principally on or below the surface of the water; (2) Moss-Lichen Wetland, dominated by mosses or lichens; (3) Emergent Wetland, dominated by emergent herbaceous angiosperms; (4) Scrub-Shrub Wetland, dominated by shrubs or small trees; and (5) Forested Wetland, dominated by large trees.The dominance type, which is named for the dominant plant or animal forms, is the lowest level of the classification hierarchy. Only examples are provided for this level; dominance types must be developed by individual users of the classification.Modifying terms applied to the classes or subclasses are essential for use of the system. In tidal areas, the type and duration of flooding are described by four water regime modifiers: subtidal, irregularly exposed, regularly flooded, and irregularly flooded. In nontidal areas, six regimes are used: permanently flooded, intermittently exposed, semipermanently flooded, seasonally flooded, saturated, temporarily flooded, intermittently flooded, and artificially flooded. A hierarchical system of water chemistry modifiers, adapted from the Venice System, is used to describe the salinity of the water. Fresh waters are further divided on the basis of pH. Use of a hierarchical system of soil modifiers taken directly from U.S. soil taxonomy is also required. Special modifiers are used where appropriate: excavated, impounded, diked, partly drained, farmed, and artificial.Regional differences important to wetland ecology are described through a regionalization that combines a system developed for inland areas by R. G. Bailey in 1976 with our Marine and Estuarine provinces.The structure of the classification allows it to be used at any of several hierarchical levels. Special data required for detailed application of the system are frequently unavailable, and thus data gathering may be prerequisite to classification. Development of rules by the user will be required for specific map scales. Dominance types and relationships of plant and animal co

Fatty acid methyl ester analysis to identify sources of soil in surface water.

PubMed

Banowetz, Gary M; Whittaker, Gerald W; Dierksen, Karen P; Azevedo, Mark D; Kennedy, Ann C; Griffith, Stephen M; Steiner, Jeffrey J

2006-01-01

Efforts to improve land-use practices to prevent contamination of surface waters with soil are limited by an inability to identify the primary sources of soil present in these waters. We evaluated the utility of fatty acid methyl ester (FAME) profiles of dry reference soils for multivariate statistical classification of soils collected from surface waters adjacent to agricultural production fields and a wooded riparian zone. Trials that compared approaches to concentrate soil from surface water showed that aluminum sulfate precipitation provided comparable yields to that obtained by vacuum filtration and was more suitable for handling large numbers of samples. Fatty acid methyl ester profiles were developed from reference soils collected from contrasting land uses in different seasons to determine whether specific fatty acids would consistently serve as variables in multivariate statistical analyses to permit reliable classification of soils. We used a Bayesian method and an independent iterative process to select appropriate fatty acids and found that variable selection was strongly impacted by the season during which soil was collected. The apparent seasonal variation in the occurrence of marker fatty acids in FAME profiles from reference soils prevented preparation of a standardized set of variables. Nevertheless, accurate classification of soil in surface water was achieved utilizing fatty acid variables identified in seasonally matched reference soils. Correlation analysis of entire chromatograms and subsequent discriminant analyses utilizing a restricted number of fatty acid variables showed that FAME profiles of soils exposed to the aquatic environment still had utility for classification at least 1 wk after submersion.

Making US Soil Taxonomy more scientifically applicable to environmental and food security issues.

NASA Astrophysics Data System (ADS)

Monger, Curtis; Lindbo, David L.; Wysocki, Doug; Schoeneberger, Phil; Libohova, Zamir

2017-04-01

US Department of Agriculture began mapping soils in the 1890s on a county-by-county basis until most of the conterminous United States was mapped by the late 1930s. This first-generation mapping was followed by a second-generation that re-mapped the US beginning in the 1940s. Soil classification during these periods evolved into the current system of Soil Taxonomy which is based on (1) soil features as natural phenomena and on (2) soil properties important for agriculture and other land uses. While this system has enabled communication among soil surveyors, the scientific applicability of Soil Taxonomy to address environmental and food security issues has been under-utilized. In particular, little effort has been exerted to understand how soil taxa interact and function together as larger units—as soil systems. Thus, much soil-geomorphic understanding that could be applied to process-based modeling remains unexploited. The challenge for soil taxonomists in the United States and elsewhere is to expand their expertise and work with modelers to explore how soil taxa are linked to each other, how they influence water, nutrient, and pollutant flow through the landscape, how they interact with ecology, and how they change with human land use.

A new landscape classification system for monitoring and assessment of pastures

USDA-ARS?s Scientific Manuscript database

Pasturelands in the United States span a broad range of climate, soils, physical sites, and management. Rather than treat each site as a unique entity, this diversity must be classified into basic units for research and management purposes. A similar system based on ecological principles is needed f...

Kubiëna's heritage: worries and hopes about micropedology (Philippe Duchaufour Medal Lecture)

NASA Astrophysics Data System (ADS)

Stoops, Georges

2010-05-01

Kubiëna's book 'Micropedology' (1938) is considered as the start of soil micromorphology, providing the first concepts allowing a systematic description and comparison of soil thin sections as a central tool for understanding soil genesis and for soil classification. The aim of this contribution is to evaluate the impact and the role of micromorphology in different fields of application, and to evaluate its progress as a discipline. The most important application in soil science has always been in the field of soil genesis. This is however affected by the declining interest (and sponsoring) for genesis nowadays. It remains however a must for studies on pedogenesis and weathering. After a strong impulse early in the nineteen sixties, caused by the study of many exotic soils and the development of new soil classification systems (7th Approximation, later Soil Taxonomy) the role of micromorphology declined together with the general interest in soil classification. Its break through as an instrument in classification did not realise. Several causes can be mentioned. On the base of experience gained in the fields of pedogenesis and classification, micromorphology became for geologists and geomorphologists an important instrument in palaeopedology, Quaternary geology and environmental reconstruction. The last two decades an enormous expansion of micromorphological studies has been noticed in the field of archaeology, not only related to ancient soils, but also to many anthropogenic materials. Archaeologists are probably the most intense users of this discipline now. Since the end of the nineteen sixties quantitative micromorphology (micromorphometry) was developed as a response to the demand for numerical data. It expanded mainly since the development of personal computers, but its wider use is essentially restricted to porosity studies related to soil physics. The complete absence of standardisation of methods and parameters hinders however its use and further expansion. Micromorphology proved also to be precious tool in monitoring experiments, both in the laboratory and in the field, often using quantitative data. Changes become visible in thin sections before they can be detected by other methods. Examples are studies on surface crust formation, effects of freezing, gypsum crystallisation and land management. Last years especially archaeologists contributed in these fields. It is also an excellent tool for controlling and interpreting data obtained by other methods. Analysis of literature and abstracts of congresses show that the last two decennia very few contributions were made related to development of micromorphological concepts and techniques. There are several causes for this situation. The bottleneck hindering use and expansion of micromorphology are both technical and theoretical. The main factors are the difficulty to acquire the necessary basic knowledge of optical techniques and micromorphological interpretation, and the difficulty to prepare good thin sections. Solutions are discussed, even as new opportunities for this discipline, at the benefit of different earth sciences.

National-Scale Hydrologic Classification & Agricultural Decision Support: A Multi-Scale Approach

NASA Astrophysics Data System (ADS)

Coopersmith, E. J.; Minsker, B.; Sivapalan, M.

2012-12-01

Classification frameworks can help organize catchments exhibiting similarity in hydrologic and climatic terms. Focusing this assessment of "similarity" upon specific hydrologic signatures, in this case the annual regime curve, can facilitate the prediction of hydrologic responses. Agricultural decision-support over a diverse set of catchments throughout the United States depends upon successful modeling of the wetting/drying process without necessitating separate model calibration at every site where such insights are required. To this end, a holistic classification framework is developed to describe both climatic variability (humid vs. arid, winter rainfall vs. summer rainfall) and the draining, storing, and filtering behavior of any catchment, including ungauged or minimally gauged basins. At the national scale, over 400 catchments from the MOPEX database are analyzed to construct the classification system, with over 77% of these catchments ultimately falling into only six clusters. At individual locations, soil moisture models, receiving only rainfall as input, produce correlation values in excess of 0.9 with respect to observed soil moisture measurements. By deploying physical models for predicting soil moisture exclusively from precipitation that are calibrated at gauged locations, overlaying machine learning techniques to improve these estimates, then generalizing the calibration parameters for catchments in a given class, agronomic decision-support becomes available where it is needed rather than only where sensing data are located.lassifications of 428 U.S. catchments on the basis of hydrologic regime data, Coopersmith et al, 2012.

Holding Capacity of Plate Anchors

DTIC Science & Technology

1980-10-01

Engineering Laboratory, Technical Report R-855. Port Hueneme, Calif., Jul 1977. Lee, H. J., and J. E . Clausner (1979). Seafloor soil sampling and...hesionless is manda- tory. Classification by the Unified Soil (lassification System is preferable. ( e ) Permeability- Required when cyclic load capacity is...mally consolidated, and (3) underconsolidated. *Formerly V.S Coast an] (; e .,letic Surk,’-,, !, S Dc ;trlnln1 ,f Commc re. 1 9 E t -. - - --- - 20 I CL I

Use of physically-based models and Soil Taxonomy to identify soil moisture classes: Problems and proposals

NASA Astrophysics Data System (ADS)

Bonfante, A.; Basile, A.; de Mascellis, R.; Manna, P.; Terribile, F.

2009-04-01

Soil classification according to Soil Taxonomy include, as fundamental feature, the estimation of soil moisture regime. The term soil moisture regime refers to the "presence or absence either of ground water or of water held at a tension of less than 1500 kPa in the soil or in specific horizons during periods of the year". In the classification procedure, defining of the soil moisture control section is the primary step in order to obtain the soil moisture regimes classification. Currently, the estimation of soil moisture regimes is carried out through simple calculation schemes, such as Newhall and Billaux models, and only in few cases some authors suggest the use of different more complex models (i.e., EPIC) In fact, in the Soil Taxonomy, the definition of the soil moisture control section is based on the wetting front position in two different conditions: the upper boundary is the depth to which a dry soil will be moistened by 2.5 cm of water within 24 hours and the lower boundary is the depth to which a dry soil will be moistened by 7.5 cm of water within 48 hours. Newhall, Billaux and EPIC models don't use physical laws to describe soil water flows, but they use a simple bucket-like scheme where the soil is divided into several compartments and water moves, instantly, only downward when the field capacity is achieved. On the other side, a large number of one-dimensional hydrological simulation models (SWAP, Cropsyst, Hydrus, MACRO, etc..) are available, tested and successfully used. The flow is simulated according to pressure head gradients through the numerical solution of the Richard's equation. These simulation models can be fruitful used to improve the study of soil moisture regimes. The aims of this work are: (i) analysis of the soil moisture control section concept by a physically based model (SWAP); (ii) comparison of the classification obtained in five different Italian pedoclimatic conditions (Mantova and Lodi in northern Italy; Salerno, Benevento and Caserta in southern Italy) applying the classical models (Newhall e Billaux) and the physically-based models (CropSyst e SWAP), The results have shown that the Soil Taxonomy scheme for the definition of the soil moisture regime is unrealistic for the considered Mediterranean soil hydrological conditions. In fact, the same classifications arise irrespective of the soil type. In this respect some suggestions on how modified the section control boundaries were formulated. Keywords: Soil moisture regimes, Newhall, Swap, Soil Taxonomy

Comparison of six fire severity classification methods using Montana and Washington wildland fires

Treesearch

Pamela G. Sikkink

2015-01-01

Fire severity classifications are used in the post-fire environment to describe fire effects, such as soil alteration or fuel consumption, on the forest floor. Most of the developed classifications are limited because they address very specific fire effects or post-burn characteristics in the burned environment. However, because fire effects vary so much among soil,...

Soil erosion modelling for NSW coastal catchments using RUSLE in a GIS environment

NASA Astrophysics Data System (ADS)

Yang, Xihua; Chapman, Greg

2006-10-01

In this study, hillslope erosion risk has been estimated for all eastern New South Wales (NSW) catchments, Australia using Revised Universal Soil Loss Equation (RUSLE) in a geographic information system (GIS) environment. Rainfall-runoff erosivity (R) factor was interpolated from NSW rainfall-erosivity contour (isoerodent) data. Soil erodibility (K) factor was based on the soil regolith stability and sediment yield classification. The classification was derived from soil landscape and related soil map data. The slope length and steepness (LS) factor was derived from high resolution digital elevation model (DEM). A fully-automated program using Arc Macro Language (AML) produced RUSLE-based LS factor grids for all coastal catchments. The outputs are comparable to the range of LS values summarised in the literature. Cover and management (C) factor and conservation support-practices (P) factor were set to one. They are intended to be allocated according to land use, ground cover and erosion control provisions for particular land management actions. The resulting erosion risk map, with pixel size of 25-m, provides unprecedented resolution of relative expected sheet and rill erosion across all NSW costal catchments and can be adapted for a range of erosion control purposes such as bushfire hazard reduction and comprehensive costal assessment.

Soil, water, and vegetation conditions in south Texas

NASA Technical Reports Server (NTRS)

Wiegand, C. L.; Gausman, H. W.; Leamer, R. W.; Richardson, A. J.; Everitt, J. H.; Gerbermann, A. H. (Principal Investigator)

1976-01-01

The author has identified the following significant results. Software development for a computer-aided crop and soil survey system is nearing completion. Computer-aided variety classification accuracies using LANDSAT-1 MSS data for a 600 hectare citrus farm were 83% for Redblush grapefruit and 91% for oranges. These accuracies indicate that there is good potential for computer-aided inventories of grapefruit and orange citrus orchards with LANDSAT-type MSS data. Mean digital values of clouds differed statistically from those for crop, soil, and water entities, and those for cloud shadows were enough lower than sunlit crop and soil to be distinguishable. The standard errors of estimate for the calibration of computer compatible tape coordinate system (pixel and record) to earth coordinate system (longitude and latitude) for 6 LANDSAT scenes ranged from 0.72 to 1.50 pixels and from 0.58 to 1.75 records.

Clay Stabilization Using the Ash of Mount Sinabung in Terms of the Value of California Bearing Ratio (CBR)

NASA Astrophysics Data System (ADS)

Hastuty, I. P.; Roesyanto, R.; Napitupulu, S. M. A.

2018-02-01

Most areas in Indonesia consist of clay soils with high plasticity so that to meet technical requirements the soil needs improvement, which is known as soil stabilization.There are three ways of soil stabilization process, i.e. mechanical, physical and chemical. In this study, chemical stabilization was performed, that was by adding stabilizing agents to the soil. The stabilizing agent used was the ash of Mount Sinabung. Since 2010 until now, Sinabung Mountain is still experiencing eruption that produces a lot of volcanic ash and it inconveniences the environment. So, it is expected that this research will be able to optimize the utilization of Sinabung ash. The purpose of this study was to investigate the effect of the addition of Mount Sinabung ash to CBR (California Bearing Ratio) value, to determine the effect of the curing time of one day and fourteen days mixture on the CBR value, and to find the mixed content with effective curing time to produce the largest CBR value. Based on this study, the soil type CL (Clay - Low Plasticity) was obtained, based on the classification of USCS (Unified Soil Classification System) and categorized as A-6 (6) based on the classification of AASHTO (American Association of State Highway and Transportation officials) with the most effective mixed stabilizer material which was the variation of 10% Mount Sinabung ash with fourteen days of curing time. The CBR value resulted from the mixture of 10% Sinabung ash that was cured within fourteen days was 8.95%. By the increase of the content of the Sinabung ash, the CBR value always improved to the level of 10%, Sinabung ash then decreased and became constant at the mixture of higher volcanic ash mixture but remained above the CBR value of the original soil.

Landmarks of History of Soil Science in Sri Lanka

NASA Astrophysics Data System (ADS)

Mapa, R.

2012-04-01

Sri Lanka is a tropical Island in the Southern tip of Indian subcontinent positioned at 50 55' to 90 50' N latitude and 790 42' to 810 53' E longitude surrounded by the Indian Ocean. It is an island 435 km in length and 224 km width consisting of a land are of 6.56 million ha with a population of 20 million. In area wise it is ranked as 118th in the world, where at present ranked as 47 in population wise and ranked 19th in population density. The country was under colonial rule under Portuguese, Dutch and British from 1505 to 1948. The majority of the people in the past and present earn their living from activities based on land, which indicates the important of the soil resource. The objective of this paper is to describe the landmarks of the history of Soil Science to highlight the achievements and failures, which is useful to enrich our present understanding of Sri Lankan soils. The landmarks of the history of Soil Science in Sri Lanka can be divided to three phases namely, the early period (prior to 1956), the middle period (1956 to 1972) and the present period (from 1972 onwards). During the early period, detailed analytical studies of coffee and tea soils were compiled, and these gave mainly information on up-country soils which led to fertilizer recommendations based on field trials. In addition, rice and forest soils were also studied in less detail. The first classification of Sri Lankan soils and a provisional soil map based on parent material was published by Joachim in 1945 which is a major landmark of history of Soil Science in Sri Lanka. In 1959 Ponnamperuma proposed a soil classification system for wetland rice soils. From 1963 to 1968 valuable information on the land resource was collected and documented by aerial resource surveys funded by Canada-Ceylon Colombo plan aid project. This covered 18 major river basins and about 1/4th of Sri Lanka, which resulted in producing excellent soil maps and information of the areas called the Kelani Aruvi Ara and Walawe basins. The provisional soil map was updated by many other workers as Moorman and Panabokke in 1961 and 1972 using this information. The soil map produced by De Alwis and Panabokke in 1972 at a scale of 1:500,000 was the soil maps mostly used during the past years During the present era, the need for classification of Soils of Sri Lanka according to international methods was felt. A major leap forward in Soil Survey, Classification leading to development of a soil data base was initiated in 1995 with the commencement of the "SRICANSOL" project which was a twining project between the Soil Science Societies of Sri Lanka and Canada. This project is now completed with detail soil maps at a scale of 1:250,000 and soil classified according to international methods for the Wet, Intermediate and Dry zones of Sri Lanka. A digital database consisting of soil profile description and physical and chemical data is under preparation for 28, 40 and 51 benchmark sites of the Wet, Intermediate and Dry zones respectively. The emphases on studies on Soil Science in the country at present is more towards environmental conservation related to soil erosion control, reducing of pollution of soil and water bodies from nitrates, pesticide residues and heavy metal accumulation. Key words: Sri Lanka, Provisional soil map

A soil map of a large watershed in China: applying digital soil mapping in a data sparse region

NASA Astrophysics Data System (ADS)

Barthold, F.; Blank, B.; Wiesmeier, M.; Breuer, L.; Frede, H.-G.

2009-04-01

Prediction of soil classes in data sparse regions is a major research challenge. With the advent of machine learning the possibilities to spatially predict soil classes have increased tremendously and given birth to new possibilities in soil mapping. Digital soil mapping is a research field that has been established during the last decades and has been accepted widely. We now need to develop tools to reduce the uncertainty in soil predictions. This is especially challenging in data sparse regions. One approach to do this is to implement soil taxonomic distance as a classification error criterion in classification and regression trees (CART) as suggested by Minasny et al. (Geoderma 142 (2007) 285-293). This approach assumes that the classification error should be larger between soils that are more dissimilar, i.e. differ in a larger number of soil properties, and smaller between more similar soils. Our study area is the Xilin River Basin, which is located in central Inner Mongolia in China. It is characterized by semi arid climate conditions and is representative for the natural occurring steppe ecosystem. The study area comprises 3600 km2. We applied a random, stratified sampling design after McKenzie and Ryan (Geoderma 89 (1999) 67-94) with landuse and topography as stratifying variables. We defined 10 sampling classes, from each class 14 replicates were randomly drawn and sampled. The dataset was split into 100 soil profiles for training and 40 soil profiles for validation. We then applied classification and regression trees (CART) to quantify the relationships between soil classes and environmental covariates. The classification tree explained 75.5% of the variance with land use and geology as most important predictor variables. Among the 8 soil classes that we predicted, the Kastanozems cover most of the area. They are predominantly found in steppe areas. However, even some of the soils at sand dune sites, which were thought to show only little soil formation, can be classified as Kastanozems. Besides the Kastanozems, Regosols are most common at the sand dune sites as well as at sites that are defined as bare soil which are characterized by little or no vegetation. Gleysols are mostly found at sites in the vicinity of the Xilin river, which are connected to the groundwater. They can also be found in small valleys or depressions where sub-surface waters from neighboring areas collect. The richest soils are found in mountain meadow areas. Pedogenetic conditions here are most favorable and lead to the formation of Chernozems with deep humic Ah horizons. Other soil types that occur in the study area are Arenosols, Calcisols, Cambisol and Phaeozems. In addition, soil taxonomic distance is implemented into the decision tree procedure as a measure of classification error. The results of incorporating taxonomic distance as a loss function in the decision tree will be compared with the standard application of the decision tree.

Soil quality and soil degradation in agricultural loess soils in Central Europe - impacts of traditional small-scale and modernized large-scale agriculture

NASA Astrophysics Data System (ADS)

Schneider, Christian

2017-04-01

The study analyzes the impact of different farming systems on soil quality and soil degradation in European loess landscapes. The analyses are based on geo-chemical soil properties, landscape metrics and geomorphological indicators. The German Middle Saxonian Loess Region represents loess landscapes whose ecological functions were shaped by land consolidation measures resulting in large-scale high-input farming systems. The Polish Proszowice Plateau is still characterized by a traditional small-scale peasant agriculture. The research areas were analyzed on different scale levels combining GIS, field, and laboratory methods. A digital terrain classification was used to identify representative catchment basins for detailed pedological studies which were focused on soil properties that responded to soil management within several years, like pH-value, total carbon (TC), total nitrogen (TN), inorganic carbon (IC), soil organic carbon (TOC=TC-IC), hot-water extractable carbon (HWC), hot-water extractable nitrogen (HWN), total phosphorus, plant-available phosphorus (P), plant-available potassium (K) and the potential cation exchange capacity (CEC). The study has shown that significant differences in major soil properties can be observed because of different fertilizer inputs and partly because of different cultivation techniques. Also the traditional system increases soil heterogeneity. Contrary to expectations the study has shown that the small-scale peasant farming system resulted in similar mean soil organic carbon and phosphorus contents like the industrialized high-input farming system. A further study could include investigations of the effects of soil amendments like herbicides and pesticide on soil degradation.

An investigation of the key parameters for predicting PV soiling losses

DOE PAGES

Micheli, Leonardo; Muller, Matthew

2017-01-25

One hundred and two environmental and meteorological parameters have been investigated and compared with the performance of 20 soiling stations installed in the USA, in order to determine their ability to predict the soiling losses occurring on PV systems. The results of this investigation showed that the annual average of the daily mean particulate matter values recorded by monitoring stations deployed near the PV systems are the best soiling predictors, with coefficients of determination ( R 2) as high as 0.82. The precipitation pattern was also found to be relevant: among the different meteorological parameters, the average length of drymore » periods had the best correlation with the soiling ratio. Lastly, a preliminary investigation of two-variable regressions was attempted and resulted in an adjusted R 2 of 0.90 when a combination of PM 2.5 and a binary classification for the average length of the dry period was introduced.« less

Clay stabilization by using gypsum and paddy husk ash with reference to UCT and CBR value

NASA Astrophysics Data System (ADS)

Roesyanto; Iskandar, R.; Hastuty, I. P.; Dianty, W. O.

2018-02-01

Clays that have low shear strength need to be stabilized in order to meet the technical requirements to serve as a subgrade material. One of the usual soil stabilization methods is by adding chemicals such as Portland cement, lime, and bitumen. The clay stabilization research was done by adding gypsum and paddy husk ash. The research goals were to find out the value of engineering properties of clay due to the addition of 2% gypsum and 2% - 15% paddy husk ash. The soil was classified as Clay - Low Plasticity (CL) based on USCS and was classified as A-7-6 (10) based on AASHTO classification system. The UCT value of original soil was 1.41 kg/cm2. While the CBR soaked and unsoaked values of original soil were 4.41% and 6.23% respectively. The research results showed the addition of paddy husk ash decreased the value of unconfined compressive strength as well as CBR. The stabilized soil by 2% gypsum and 0% paddy husk ash gave maximum UCT value of 1.67 kg/cm2, while the maximum value of CBR were found 6.71% for CBR soaked and 8.00% for CBR unsoaked. The addition of paddy husk ash did not alter the soil classification according to AASHTO or USCS, even degrade the engineering properties of original soil.

A simulation study of scene confusion factors in sensing soil moisture from orbital radar

NASA Technical Reports Server (NTRS)

Ulaby, F. T. (Principal Investigator); Dobson, M. C.; Moezzi, S.; Roth, F. T.

1983-01-01

Simulated C-band radar imagery for a 124-km by 108-km test site in eastern Kansas is used to classify soil moisture. Simulated radar resolutions are 100 m by 100 m, 1 km by 1km, and 3 km by 3 km. Distributions of actual near-surface soil moisture are established daily for a 23-day accounting period using a water budget model. Within the 23-day period, three orbital radar overpasses are simulated roughly corresponding to generally moist, wet, and dry soil moisture conditions. The radar simulations are performed by a target/sensor interaction model dependent upon a terrain model, land-use classification, and near-surface soil moisture distribution. The accuracy of soil-moisture classification is evaluated for each single-date radar observation and also for multi-date detection of relative soil moisture change. In general, the results for single-date moisture detection show that 70% to 90% of cropland can be correctly classified to within +/- 20% of the true percent of field capacity. For a given radar resolution, the expected classification accuracy is shown to be dependent upon both the general soil moisture condition and also the geographical distribution of land-use and topographic relief. An analysis of cropland, urban, pasture/rangeland, and woodland subregions within the test site indicates that multi-temporal detection of relative soil moisture change is least sensitive to classification error resulting from scene complexity and topographic effects.

Estimating persistence of brominated and chlorinated organic pollutants in air, water, soil, and sediments with the QSPR-based classification scheme.

PubMed

Puzyn, T; Haranczyk, M; Suzuki, N; Sakurai, T

2011-02-01

We have estimated degradation half-lives of both brominated and chlorinated dibenzo-p-dioxins (PBDDs and PCDDs), furans (PBDFs and PCDFs), biphenyls (PBBs and PCBs), naphthalenes (PBNs and PCNs), diphenyl ethers (PBDEs and PCDEs) as well as selected unsubstituted polycyclic aromatic hydrocarbons (PAHs) in air, surface water, surface soil, and sediments (in total of 1,431 compounds in four compartments). Next, we compared the persistence between chloro- (relatively well-studied) and bromo- (less studied) analogs. The predictions have been performed based on the quantitative structure-property relationship (QSPR) scheme with use of k-nearest neighbors (kNN) classifier and the semi-quantitative system of persistence classes. The classification models utilized principal components derived from the principal component analysis of a set of 24 constitutional and quantum mechanical descriptors as input variables. Accuracies of classification (based on an external validation) were 86, 85, 87, and 75% for air, surface water, surface soil, and sediments, respectively. The persistence of all chlorinated species increased with increasing halogenation degree. In the case of brominated organic pollutants (Br-OPs), the trend was the same for air and sediments. However, we noticed that the opposite trend for persistence in surface water and soil. The results suggest that, due to high photoreactivity of C-Br chemical bonds, photolytic processes occurring in surface water and soil are able to play significant role in transforming and removing Br-OPs from these compartments. This contribution is the first attempt of classifying together Br-OPs and Cl-OPs according to their persistence, in particular, environmental compartments.

Data-driven modeling of hydroclimatic trends and soil moisture: Multi-scale data integration and decision support

NASA Astrophysics Data System (ADS)

Coopersmith, Evan Joseph

The techniques and information employed for decision-making vary with the spatial and temporal scope of the assessment required. In modern agriculture, the farm owner or manager makes decisions on a day-to-day or even hour-to-hour basis for dozens of fields scattered over as much as a fifty-mile radius from some central location. Following precipitation events, land begins to dry. Land-owners and managers often trace serpentine paths of 150+ miles every morning to inspect the conditions of their various parcels. His or her objective lies in appropriate resource usage -- is a given tract of land dry enough to be workable at this moment or would he or she be better served waiting patiently? Longer-term, these owners and managers decide upon which seeds will grow most effectively and which crops will make their operations profitable. At even longer temporal scales, decisions are made regarding which fields must be acquired and sold and what types of equipment will be necessary in future operations. This work develops and validates algorithms for these shorter-term decisions, along with models of national climate patterns and climate changes to enable longer-term operational planning. A test site at the University of Illinois South Farms (Urbana, IL, USA) served as the primary location to validate machine learning algorithms, employing public sources of precipitation and potential evapotranspiration to model the wetting/drying process. In expanding such local decision support tools to locations on a national scale, one must recognize the heterogeneity of hydroclimatic and soil characteristics throughout the United States. Machine learning algorithms modeling the wetting/drying process must address this variability, and yet it is wholly impractical to construct a separate algorithm for every conceivable location. For this reason, a national hydrological classification system is presented, allowing clusters of hydroclimatic similarity to emerge naturally from annual regime curve data and facilitate the development of cluster-specific algorithms. Given the desire to enable intelligent decision-making at any location, this classification system is developed in a manner that will allow for classification anywhere in the U.S., even in an ungauged basin. Daily time series data from 428 catchments in the MOPEX database are analyzed to produce an empirical classification tree, partitioning the United States into regions of hydroclimatic similarity. In constructing a classification tree based upon 55 years of data, it is important to recognize the non-stationary nature of climate data. The shifts in climatic regimes will cause certain locations to shift their ultimate position within the classification tree, requiring decision-makers to alter land usage, farming practices, and equipment needs, and algorithms to adjust accordingly. This work adapts the classification model to address the issue of regime shifts over larger temporal scales and suggests how land-usage and farming protocol may vary from hydroclimatic shifts in decades to come. Finally, the generalizability of the hydroclimatic classification system is tested with a physically-based soil moisture model calibrated at several locations throughout the continental United States. The soil moisture model is calibrated at a given site and then applied with the same parameters at other sites within and outside the same hydroclimatic class. The model's performance deteriorates minimally if the calibration and validation location are within the same hydroclimatic class, but deteriorates significantly if the calibration and validates sites are located in different hydroclimatic classes. These soil moisture estimates at the field scale are then further refined by the introduction of LiDAR elevation data, distinguishing faster-drying peaks and ridges from slower-drying valleys. The inclusion of LiDAR enabled multiple locations within the same field to be predicted accurately despite non-identical topography. This cross-application of parametric calibrations and LiDAR-driven disaggregation facilitates decision-support at locations without proximally-located soil moisture sensors.

A laboratory procedure for measuring and georeferencing soil colour

NASA Astrophysics Data System (ADS)

Marques-Mateu, A.; Balaguer-Puig, M.; Moreno-Ramon, H.; Ibanez-Asensio, S.

2015-04-01

Remote sensing and geospatial applications very often require ground truth data to assess outcomes from spatial analyses or environmental models. Those data sets, however, may be difficult to collect in proper format or may even be unavailable. In the particular case of soil colour the collection of reliable ground data can be cumbersome due to measuring methods, colour communication issues, and other practical factors which lead to a lack of standard procedure for soil colour measurement and georeferencing. In this paper we present a laboratory procedure that provides colour coordinates of georeferenced soil samples which become useful in later processing stages of soil mapping and classification from digital images. The procedure requires a laboratory setup consisting of a light booth and a trichromatic colorimeter, together with a computer program that performs colour measurement, storage, and colour space transformation tasks. Measurement tasks are automated by means of specific data logging routines which allow storing recorded colour data in a spatial format. A key feature of the system is the ability of transforming between physically-based colour spaces and the Munsell system which is still the standard in soil science. The working scheme pursues the automation of routine tasks whenever possible and the avoidance of input mistakes by means of a convenient layout of the user interface. The program can readily manage colour and coordinate data sets which eventually allow creating spatial data sets. All the tasks regarding data joining between colorimeter measurements and samples locations are executed by the software in the background, allowing users to concentrate on samples processing. As a result, we obtained a robust and fully functional computer-based procedure which has proven a very useful tool for sample classification or cataloging purposes as well as for integrating soil colour data with other remote sensed and spatial data sets.

Predictive mapping of soil organic carbon in wet cultivated lands using classification-tree based models: the case study of Denmark.

PubMed

Bou Kheir, Rania; Greve, Mogens H; Bøcher, Peder K; Greve, Mette B; Larsen, René; McCloy, Keith

2010-05-01

Soil organic carbon (SOC) is one of the most important carbon stocks globally and has large potential to affect global climate. Distribution patterns of SOC in Denmark constitute a nation-wide baseline for studies on soil carbon changes (with respect to Kyoto protocol). This paper predicts and maps the geographic distribution of SOC across Denmark using remote sensing (RS), geographic information systems (GISs) and decision-tree modeling (un-pruned and pruned classification trees). Seventeen parameters, i.e. parent material, soil type, landscape type, elevation, slope gradient, slope aspect, mean curvature, plan curvature, profile curvature, flow accumulation, specific catchment area, tangent slope, tangent curvature, steady-state wetness index, Normalized Difference Vegetation Index (NDVI), Normalized Difference Wetness Index (NDWI) and Soil Color Index (SCI) were generated to statistically explain SOC field measurements in the area of interest (Denmark). A large number of tree-based classification models (588) were developed using (i) all of the parameters, (ii) all Digital Elevation Model (DEM) parameters only, (iii) the primary DEM parameters only, (iv), the remote sensing (RS) indices only, (v) selected pairs of parameters, (vi) soil type, parent material and landscape type only, and (vii) the parameters having a high impact on SOC distribution in built pruned trees. The best constructed classification tree models (in the number of three) with the lowest misclassification error (ME) and the lowest number of nodes (N) as well are: (i) the tree (T1) combining all of the parameters (ME=29.5%; N=54); (ii) the tree (T2) based on the parent material, soil type and landscape type (ME=31.5%; N=14); and (iii) the tree (T3) constructed using parent material, soil type, landscape type, elevation, tangent slope and SCI (ME=30%; N=39). The produced SOC maps at 1:50,000 cartographic scale using these trees are highly matching with coincidence values equal to 90.5% (Map T1/Map T2), 95% (Map T1/Map T3) and 91% (Map T2/Map T3). The overall accuracies of these maps once compared with field observations were estimated to be 69.54% (Map T1), 68.87% (Map T2) and 69.41% (Map T3). The proposed tree models are relatively simple, and may be also applied to other areas. Copyright 2010 Elsevier Ltd. All rights reserved.

Corn and soybean Landsat MSS classification performance as a function of scene characteristics

NASA Technical Reports Server (NTRS)

Batista, G. T.; Hixson, M. M.; Bauer, M. E.

1982-01-01

In order to fully utilize remote sensing to inventory crop production, it is important to identify the factors that affect the accuracy of Landsat classifications. The objective of this study was to investigate the effect of scene characteristics involving crop, soil, and weather variables on the accuracy of Landsat classifications of corn and soybeans. Segments sampling the U.S. Corn Belt were classified using a Gaussian maximum likelihood classifier on multitemporally registered data from two key acquisition periods. Field size had a strong effect on classification accuracy with small fields tending to have low accuracies even when the effect of mixed pixels was eliminated. Other scene characteristics accounting for variability in classification accuracy included proportions of corn and soybeans, crop diversity index, proportion of all field crops, soil drainage, slope, soil order, long-term average soybean yield, maximum yield, relative position of the segment in the Corn Belt, weather, and crop development stage.

Soil organic matter degradation and enzymatic profiles of intertidal and subaqueous soils

NASA Astrophysics Data System (ADS)

Ferronato, Chiara; Marinari, Sara; Bello, Diana; Vianello, Gilmo; Trasar-Cepeda, Carmen; Vittori Antisari, Livia

2017-04-01

The interest on intertidal and subaqueous soils has recently arisen because of the climate changes forecasts. The preservation of these habitats represents an important challenge for the future of humanity, because these systems represent an important global C sink since soil organic matter (SOM) on intertidal and subaqueous soils undergoes very slow degradation rates due to oxygen limitation. Publications on SOM cycle in saltmarshes are very scarce because of the difficulties involved on those studies i.e. the interaction of many abiotic and biotic factors (e.g., redox changes, water and bio-turbation processes, etc) and stressors (e.g., salinity and anoxia). However, saltmarshes constitute an unique natural system to observe the influence of anoxic conditions on SOM degradation, because the tide fluctuations on the soil surface allow the formation of provisionally or permanently submerged soils. With the aim to investigate the quality of SOM in subaqueous soils, triplicates of subaqueous soils (SASs), intertidal soils (ITSs) and terrestrial soils (TESs) were collected in the saltmarshes of the Baiona Lagoon (Northern Italy) and classified according to their pedogenetic horizons. The SOM quality on each soil horizon was investigated by quantifying SOM, total and water-soluble organic carbon (TOC, WSC) and microbial biomass carbon (MBC). Given the contribution of soil enzymes to the degradation of SOM, some enzymatic assays were also performed. Thereafter, soil classification and humus morpho-functional classification were used to join together similar soil profiles to facilitate the description and discussion of results. Soils were ranked as Aquent or Wassent Entisols, with an A/AC/C pedosequence. SOM, TOC and MBC were statistically higher in A than in AC and C horizons. Among the A horizons, ITSs were those showing the highest values for these parameters (11% TOC, 1.6 mg kg-1 MBC, 0.9 mg kg-1 WSC). These results, combined with the morpho-functional classification of epipedons, reflect the influence of the type of annual biomass depositions on ITSs (i.e. Salicornia europaea), but also the important role of the tide oscillation that promotes the continuous alternation of red-ox exchanges and thus fasten the organic matter turnover in ITSs. On these pedons, invertase was the most effective enzymes (11.6 μmol glucose g-1h-1). Moreover, in SASs and ITSs, most of the activities linked to the degradation of exoskeletons and fungi (e.g. chitinase) increase along the soil profile, probably due to the disrupting effect of water on the soil and to the type of SOM in saltmarshes soils. By considering the specific activity (enzymatic activity/TOC content), data showed how SASs, ITSs and TESs had different oxidoreductases and hydrolases trends, suggesting a different path and effectiveness of SOM degradation, which probably depends both on the soil hydric regime, and on the different type of organic compounds. A particular increase of catalase and invertase specific activities along the soil profiles, suggests the presence of microaerophilic environment in some saturated AC and C sandy horizons but generally, it was observed a gradual decrease of biochemical alteration of the SOM by enzymatic activities along the soil profile due to the progressive restriction of the edaphic conditions.

Chemical sensing system for classification of minelike objects by explosives detection

NASA Astrophysics Data System (ADS)

Chambers, William B.; Rodacy, Philip J.; Jones, Edwin E.; Gomez, Bernard J.; Woodfin, Ronald L.

1998-09-01

Sandia National Laboratories has conducted research in chemical sensing and analysis of explosives for many years. Recently, that experience has been directed towards detecting mines and unexploded ordnance (UXO) by sensing the low-level explosive signatures associated with these objects. Our focus has been on the classification of UXO in shallow water and anti-personnel/anti tank mines on land. The objective of this work is to develop a field portable chemical sensing system which can be used to examine mine-like objects (MLO) to determine whether there are explosive molecules associated with the MLO. Two sampling subsystems have been designed, one for water collection and one for soil/vapor sampling. The water sampler utilizes a flow-through chemical adsorbent canister to extract and concentrate the explosive molecules. Explosive molecules are thermally desorbed from the concentrator and trapped in a focusing stage for rapid desorption into an ion-mobility spectrometer (IMS). We will describe a prototype system which consists of a sampler, concentrator-focuser, and detector. The soil sampler employs a light-weight probe for extracting and concentrating explosive vapor from the soil in the vicinity of an MLO. The chemical sensing system is capable of sub-part-per-billion detection of TNT and related explosive munition compounds. We will present the results of field and laboratory tests on buried landmines, which demonstrate our ability to detect the explosive signatures associated with these objects.

Edaphostat: interactive ecological analysis of soil organism occurrences and preferences from the Edaphobase data warehouse

PubMed Central

Scholz-Starke, Björn; Burkhardt, Ulrich; Lesch, Stephan; Rick, Sebastian; Russell, David; Roß-Nickoll, Martina; Ottermanns, Richard

2017-01-01

Abstract The Edaphostat web application allows interactive and dynamic analyses of soil organism data stored in the Edaphobase data warehouse. It is part of the Edaphobase web application and can be accessed by any modern browser. The tool combines data from different sources (publications, field studies and museum collections) and allows species preferences along various environmental gradients (i.e. C/N ratio and pH) and classification systems (habitat type and soil type) to be analyzed. Database URL: Edaphostat is part of the Edaphobase Web Application available at https://portal.edaphobase.org PMID:29220469

Characteristic variations in reflectance of surface soils

NASA Technical Reports Server (NTRS)

Stoner, E. R.; Baumgardner, M. F. (Principal Investigator)

1982-01-01

Surface soil samples from a wide range of naturally occurring soils were obtained for the purpose of studying the characteristic variations in soil reflectance as these variations relate to other soil properties and soil classification. A total 485 soil samples from the U.S. and Brazil representing 30 suborders of the 10 orders of 'Soil Taxonomy' was examined. The spectral bidirectional reflectance factor was measured on uniformly moist soils over the 0.52 to 2.32 micron wavelength range with a spectroradiometer adapted for indoor use. Five distinct soil spectral reflectance curve forms were identified according to curve shape, the presence or absence of absorption bands, and the predominance of soil organic matter and iron oxide composition. These curve forms were further characterized according to generically homogeneous soil properties in a manner similar to the subdivisions at the suborder level of 'Soil Taxonomy'. Results indicate that spectroradiometric measurements of soil spectral bidirectional reflectance factor can be used to characterize soil reflectance in terms that are meaningful to soil classification, genesis, and survey.

Hyperparameterization of soil moisture statistical models for North America with Ensemble Learning Models (Elm)

NASA Astrophysics Data System (ADS)

Steinberg, P. D.; Brener, G.; Duffy, D.; Nearing, G. S.; Pelissier, C.

2017-12-01

Hyperparameterization, of statistical models, i.e. automated model scoring and selection, such as evolutionary algorithms, grid searches, and randomized searches, can improve forecast model skill by reducing errors associated with model parameterization, model structure, and statistical properties of training data. Ensemble Learning Models (Elm), and the related Earthio package, provide a flexible interface for automating the selection of parameters and model structure for machine learning models common in climate science and land cover classification, offering convenient tools for loading NetCDF, HDF, Grib, or GeoTiff files, decomposition methods like PCA and manifold learning, and parallel training and prediction with unsupervised and supervised classification, clustering, and regression estimators. Continuum Analytics is using Elm to experiment with statistical soil moisture forecasting based on meteorological forcing data from NASA's North American Land Data Assimilation System (NLDAS). There Elm is using the NSGA-2 multiobjective optimization algorithm for optimizing statistical preprocessing of forcing data to improve goodness-of-fit for statistical models (i.e. feature engineering). This presentation will discuss Elm and its components, including dask (distributed task scheduling), xarray (data structures for n-dimensional arrays), and scikit-learn (statistical preprocessing, clustering, classification, regression), and it will show how NSGA-2 is being used for automate selection of soil moisture forecast statistical models for North America.

Successional stage of biological soil crusts: an accurate indicator of ecohydrological condition

USGS Publications Warehouse

Belnap, Jayne; Wilcox, Bradford P.; Van Scoyoc, Matthew V.; Phillips, Susan L.

2013-01-01

Biological soil crusts are a key component of many dryland ecosystems. Following disturbance, biological soil crusts will recover in stages. Recently, a simple classification of these stages has been developed, largely on the basis of external features of the crusts, which reflects their level of development (LOD). The classification system has six LOD classes, from low (1) to high (6). To determine whether the LOD of a crust is related to its ecohydrological function, we used rainfall simulation to evaluate differences in infiltration, runoff, and erosion among crusts in the various LODs, across a range of soil depths and with different wetting pre-treatments. We found large differences between the lowest and highest LODs, with runoff and erosion being greatest from the lowest LOD. Under dry antecedent conditions, about 50% of the water applied ran off the lowest LOD plots, whereas less than 10% ran off the plots of the two highest LODs. Similarly, sediment loss was 400 g m-2 from the lowest LOD and almost zero from the higher LODs. We scaled up the results from these simulations using the Rangeland Hydrology and Erosion Model. Modelling results indicate that erosion increases dramatically as slope length and gradient increase, especially beyond the threshold values of 10 m for slope length and 10% for slope gradient. Our findings confirm that the LOD classification is a quick, easy, nondestructive, and accurate index of hydrological condition and should be incorporated in field and modelling assessments of ecosystem health.

Investigating the relationship between a soils classification and the spatial parameters of a conceptual catchment-scale hydrological model

NASA Astrophysics Data System (ADS)

Dunn, S. M.; Lilly, A.

2001-10-01

There are now many examples of hydrological models that utilise the capabilities of Geographic Information Systems to generate spatially distributed predictions of behaviour. However, the spatial variability of hydrological parameters relating to distributions of soils and vegetation can be hard to establish. In this paper, the relationship between a soil hydrological classification Hydrology of Soil Types (HOST) and the spatial parameters of a conceptual catchment-scale model is investigated. A procedure involving inverse modelling using Monte-Carlo simulations on two catchments is developed to identify relative values for soil related parameters of the DIY model. The relative values determine the internal variability of hydrological processes as a function of the soil type. For three out of the four soil parameters studied, the variability between HOST classes was found to be consistent across two catchments when tested independently. Problems in identifying values for the fourth 'fast response distance' parameter have highlighted a potential limitation with the present structure of the model. The present assumption that this parameter can be related simply to soil type rather than topography appears to be inadequate. With the exclusion of this parameter, calibrated parameter sets from one catchment can be converted into equivalent parameter sets for the alternate catchment on the basis of their HOST distributions, to give a reasonable simulation of flow. Following further testing on different catchments, and modifications to the definition of the fast response distance parameter, the technique provides a methodology whereby it is possible to directly derive spatial soil parameters for new catchments.

A Round Robin evaluation of AMSR-E soil moisture retrievals

NASA Astrophysics Data System (ADS)

Mittelbach, Heidi; Hirschi, Martin; Nicolai-Shaw, Nadine; Gruber, Alexander; Dorigo, Wouter; de Jeu, Richard; Parinussa, Robert; Jones, Lucas A.; Wagner, Wolfgang; Seneviratne, Sonia I.

2014-05-01

Large-scale and long-term soil moisture observations based on remote sensing are promising data sets to investigate and understand various processes of the climate system including the water and biochemical cycles. Currently, the ESA Climate Change Initiative for soil moisture develops and evaluates a consistent global long-term soil moisture data set, which is based on merging passive and active remotely sensed soil moisture. Within this project an inter-comparison of algorithms for AMSR-E and ASCAT Level 2 products was conducted separately to assess the performance of different retrieval algorithms. Here we present the inter-comparison of AMSR-E Level 2 soil moisture products. These include the public data sets from University of Montana (UMT), Japan Aerospace and Space Exploration Agency (JAXA), VU University of Amsterdam (VUA; two algorithms) and National Aeronautics and Space Administration (NASA). All participating algorithms are applied to the same AMSR-E Level 1 data set. Ascending and descending paths of scaled surface soil moisture are considered and evaluated separately in daily and monthly resolution over the 2007-2011 time period. Absolute values of soil moisture as well as their long-term anomalies (i.e. removing the mean seasonal cycle) and short-term anomalies (i.e. removing a five weeks moving average) are evaluated. The evaluation is based on conventional measures like correlation and unbiased root-mean-square differences as well as on the application of the triple collocation method. As reference data set, surface soil moisture of 75 quality controlled soil moisture sites from the International Soil Moisture Network (ISMN) are used, which cover a wide range of vegetation density and climate conditions. For the application of the triple collocation method, surface soil moisture estimates from the Global Land Data Assimilation System are used as third independent data set. We find that the participating algorithms generally display a better performance for the descending compared to the ascending paths. A first classification of the sites defined by geographical locations show that the algorithms have a very similar average performance. Further classifications of the sites by land cover types and climate regions will be conducted which might result in a more diverse performance of the algorithms.

A European Humus Forms Reference Base

NASA Astrophysics Data System (ADS)

Zanella, A.; Englisch, M.; Ponge, J.-F.; Jabiol, B.; Sartori, G.; Gardi, C.

2012-04-01

From 2003 on, a panel of experts in humus and humus dynamics (Humus group) has been working about a standardisation and improvement of existing national humus classifications. Some important goals have been reached, in order to share data and experiences: a) definition of specific terms; b) description of 15 types of diagnostic horizons; c) of 10 basic humus forms references; d) subdivision of each main reference in 2-4 sub-unities; e) elaboration of a general European Humus Form Reference Base (http://hal-agroparistech.archives-ouvertes.fr/docs/00/56/17/95/PDF/Humus_Forms_ERB_31_01_2011.pdf); f) publication of the scientific significance of this base of classification as an article [A European morpho-functional classification of humus forms. Geoderma, 164 (3-4), 138-145]. The classification will be updated every 2 years and presently the Humus group is assessing biological (general: soil, vegetation, biome; specific: fungi, bacteria, pedofauna), physical (air temperature, rainfall) and chemical (pH, mineral elements, organic matter, quality and quantity of humic components…) factors which characterize basic humus forms and their varieties. The content of the new version of the classification is planned to be more "practical", like an ecological manual which lists associated humus forms and environmental data in the aim to contribute to a more precise environmental diagnosis of every analysed terrestrial and semiterrestrial European ecosystem. The Humus group is also involved in an endeavour to include humus forms in the World Reference Base for Soils (WRB-FAO) according to nomenclatural principles erected for soil profiles. Thirty basic references have been defined, complemented by a set of qualifiers (prefixes and suffixes), allowing to classify European humus forms and probably a large majority of humus forms known worldwide. The principles of the classification, the diagnostic horizons and humus forms main references are presented at the General Assembly of the European Geosciences Union with the aim to stimulate members' curiosity. Interested people are invited to test the classification system in various field areas and to collaborate with the Humus group. Critical observations and field data/impressions are welcome as every other suggestions which can help in elaborating the 2013 version of the European humus forms classification.

The Application of Remote Sensing Data to GIS Studies of Land Use, Land Cover, and Vegetation Mapping in the State of Hawaii

NASA Technical Reports Server (NTRS)

Hogan, Christine A.

1996-01-01

A land cover-vegetation map with a base classification system for remote sensing use in a tropical island environment was produced of the island of Hawaii for the State of Hawaii to evaluate whether or not useful land cover information can be derived from Landsat TM data. In addition, an island-wide change detection mosaic combining a previously created 1977 MSS land classification with the TM-based classification was produced. In order to reach the goal of transferring remote sensing technology to State of Hawaii personnel, a pilot project was conducted while training State of Hawaii personnel in remote sensing technology and classification systems. Spectral characteristics of young island land cover types were compared to determine if there are differences in vegetation types on lava, vegetation types on soils, and barren lava from soils, and if they can be detected remotely, based on differences in pigments detecting plant physiognomic type, health, stress at senescence, heat, moisture level, and biomass. Geographic information systems (GIS) and global positioning systems (GPS) were used to assist in image rectification and classification. GIS was also used to produce large-format color output maps. An interactive GIS program was written to provide on-line access to scanned photos taken at field sites. The pilot project found Landsat TM to be a credible source of land cover information for geologically young islands, and TM data bands are effective in detecting spectral characteristics of different land cover types through remote sensing. Large agriculture field patterns were resolved and mapped successfully from wildland vegetation, but small agriculture field patterns were not. Additional processing was required to work with the four TM scenes from two separate orbits which span three years, including El Nino and drought dates. Results of the project emphasized the need for further land cover and land use processing and research. Change in vegetation composition was noted in the change detection image.

Remote Sensing Monitoring of Changes in Soil Salinity: A Case Study in Inner Mongolia, China.

PubMed

Wu, Jingwei; Vincent, Bernard; Yang, Jinzhong; Bouarfa, Sami; Vidal, Alain

2008-11-07

This study used archived remote sensing images to depict the history of changes in soil salinity in the Hetao Irrigation District in Inner Mongolia, China, with the purpose of linking these changes with land and water management practices and to draw lessons for salinity control. Most data came from LANDSAT satellite images taken in 1973, 1977, 1988, 1991, 1996, 2001, and 2006. In these years salt-affected areas were detected using a normal supervised classification method. Corresponding cropped areas were detected from NVDI (Normalized Difference Vegetation Index) values using an unsupervised method. Field samples and agricultural statistics were used to estimate the accuracy of the classification. Historical data concerning irrigation/drainage and the groundwater table were used to analyze the relation between changes in soil salinity and land and water management practices. Results showed that: (1) the overall accuracy of remote sensing in detecting soil salinity was 90.2%, and in detecting cropped area, 98%; (2) the installation/innovation of the drainage system did help to control salinity; and (3) a low ratio of cropped land helped control salinity in the Hetao Irrigation District. These findings suggest that remote sensing is a useful tool to detect soil salinity and has potential in evaluating and improving land and water management practices.

Comparative analysis of tree classification models for detecting fusarium oxysporum f. sp cubense (TR4) based on multi soil sensor parameters

NASA Astrophysics Data System (ADS)

Estuar, Maria Regina Justina; Victorino, John Noel; Coronel, Andrei; Co, Jerelyn; Tiausas, Francis; Señires, Chiara Veronica

2017-09-01

Use of wireless sensor networks and smartphone integration design to monitor environmental parameters surrounding plantations is made possible because of readily available and affordable sensors. Providing low cost monitoring devices would be beneficial, especially to small farm owners, in a developing country like the Philippines, where agriculture covers a significant amount of the labor market. This study discusses the integration of wireless soil sensor devices and smartphones to create an application that will use multidimensional analysis to detect the presence or absence of plant disease. Specifically, soil sensors are designed to collect soil quality parameters in a sink node from which the smartphone collects data from via Bluetooth. Given these, there is a need to develop a classification model on the mobile phone that will report infection status of a soil. Though tree classification is the most appropriate approach for continuous parameter-based datasets, there is a need to determine whether tree models will result to coherent results or not. Soil sensor data that resides on the phone is modeled using several variations of decision tree, namely: decision tree (DT), best-fit (BF) decision tree, functional tree (FT), Naive Bayes (NB) decision tree, J48, J48graft and LAD tree, where decision tree approaches the problem by considering all sensor nodes as one. Results show that there are significant differences among soil sensor parameters indicating that there are variances in scores between the infected and uninfected sites. Furthermore, analysis of variance in accuracy, recall, precision and F1 measure scores from tree classification models homogeneity among NBTree, J48graft and J48 tree classification models.

A history of Soil Survey in England and Wales

NASA Astrophysics Data System (ADS)

Hallett, S.; Deeks, L.

2012-04-01

Early soil mapping in Britain was dominated, as in the USA, by soil texture with maps dating back to the early 1900's identifying surface texture and parent rock materials. Only in the 1920's did Dokuchaev's work in Russia involving soil morphology and the development of the soil profile start to gain popularity, drawing in the influence of climate and topography on pedogenesis. Intentions to create a formal body at this time responsible for soil survey were not implemented and progress remained slow. However, in 1939 definite steps were taken to address this and the soil survey was created. In 1947, its activities were transferred from Bangor to the research branch of the Rothamsted experimental station in Hertfordshire under Professor G.W. Robinson. Soon after, a number of regional offices were also established to act as a link with the National Agricultural Advisory Service. At this time a Pedology Department was established at Rothamsted, focussing on petrological, X-ray, spectrographic and chemical analyses. Although not a Rothamsted Department itself, the Survey did fall under the 'Lawes Agricultural Trust'. A Soil Survey Research Advisory Board was also formed to act as a liaison with the Agricultural Field Council. In Scotland by contrast, soil survey activities became centred on the Macaulay Institute in Aberdeen. Developments in the survey of British soils were accompanied in parallel by the development of soil classification systems. In 1930 a Soils Correlation Committee had been formed to ensure consistency in methods and naming of soil series and to ensure the classification was applied uniformly. In England and Wales the zonal system adopted was similar to that used in the USA, where soil series were named after the location where they were first described. American soil scientists such as Veitch and Lee provided stimulus to the development of mapping methods. In Scotland a differing classification was adopted, being similar to that used in Canada, recognising the importance of the soil drainage characteristics within areas of similar parent material. This led to the adoption of the soil catena approach and the usage of soil 'associations'. With Britain entering the Second World War in 1939, there followed the almost complete cessation of survey activities and it was only in the aftermath of that war that recruitment of surveyors could re-commence. The first Soil Survey Field Handbook was published in 1940. Systematic and formal national soil survey activities across both England and Wales can be dated back to 1947 when work commenced to provide a complete picture of the soil resources of the two countries. Mapping at 1:25,000 scale, almost half the land was covered when, in 1979, the survey received instructions, together with the Scottish survey, to complete respective national maps at 1:250,000, which were published in the early 1980s. Attention then turned again to mapping lowland areas in more detail as well as specialised and thematic maps. However, in 1987 systematic survey was terminated and staff of the Soil Survey of England and Wales disbanded to form the Soil Survey and Land Research Centre (SSLRC) at what became Cranfield University - where its successor, the National Soil Resources Institute (NSRI) operates currently.

Estimation of Compaction Parameters Based on Soil Classification

NASA Astrophysics Data System (ADS)

Lubis, A. S.; Muis, Z. A.; Hastuty, I. P.; Siregar, I. M.

2018-02-01

Factors that must be considered in compaction of the soil works were the type of soil material, field control, maintenance and availability of funds. Those problems then raised the idea of how to estimate the density of the soil with a proper implementation system, fast, and economical. This study aims to estimate the compaction parameter i.e. the maximum dry unit weight (γ dmax) and optimum water content (Wopt) based on soil classification. Each of 30 samples were being tested for its properties index and compaction test. All of the data’s from the laboratory test results, were used to estimate the compaction parameter values by using linear regression and Goswami Model. From the research result, the soil types were A4, A-6, and A-7 according to AASHTO and SC, SC-SM, and CL based on USCS. By linear regression, the equation for estimation of the maximum dry unit weight (γdmax *)=1,862-0,005*FINES- 0,003*LL and estimation of the optimum water content (wopt *)=- 0,607+0,362*FINES+0,161*LL. By Goswami Model (with equation Y=mLogG+k), for estimation of the maximum dry unit weight (γdmax *) with m=-0,376 and k=2,482, for estimation of the optimum water content (wopt *) with m=21,265 and k=-32,421. For both of these equations a 95% confidence interval was obtained.

Taxonomic classification of world map units in crop producing areas of Argentina and Brazil with representative US soil series and major land resource areas in which they occur

NASA Technical Reports Server (NTRS)

Huckle, H. F. (Principal Investigator)

1980-01-01

The most probable current U.S. taxonomic classification of the soils estimated to dominate world soil map units (WSM)) in selected crop producing states of Argentina and Brazil are presented. Representative U.S. soil series the units are given. The map units occurring in each state are listed with areal extent and major U.S. land resource areas in which similar soils most probably occur. Soil series sampled in LARS Technical Report 111579 and major land resource areas in which they occur with corresponding similar WSM units at the taxonomic subgroup levels are given.

24 CFR 3285.4 - Incorporation by reference (IBR).

Code of Federal Regulations, 2012 CFR

2012-04-01

...-6600, fax number (253) 565-7265. (1) PS1-95, Construction and Industrial Plywood (with typical APA... for Engineering Purposes (Unified Soil Classification System), 2000, IBR approved for the table at... purchase from the Structural Engineering Institute/American Society of Civil Engineers (SEI/ASCE), 1801...

24 CFR 3285.4 - Incorporation by reference (IBR).

Code of Federal Regulations, 2011 CFR

2011-04-01

...-6600, fax number (253) 565-7265. (1) PS1-95, Construction and Industrial Plywood (with typical APA... for Engineering Purposes (Unified Soil Classification System), 2000, IBR approved for the table at... purchase from the Structural Engineering Institute/American Society of Civil Engineers (SEI/ASCE), 1801...

Machine-assisted analysis of Landsat data in the study of crop-soils relationships

USGS Publications Warehouse

Draeger, William C.

1976-01-01

To date, relatively few studies have dealt with crop-soil interactions as they affect the appearance of agricultural areas on Landsat imagery, and hence crop and soil classification or the analysis of agricultural land use.The Image 100, a computer-based data analysis system which allows an interpreter to interact directly and rapidly with Landsat computer compatible tape data, provided a tool to assist in the evaluation of the extent and significance of these interactions. Used with timely and accurate ground data, the system made possible a determination of the variability in crop spectral appearance, from soil type to soil type, as recorded on Landsat data. Information was provided in the form of spectral distribution histrograms for each crop-soil class on each Landsat band. Several crop categories in a test area in  rookings County, South Dakota, were classified using training fields that were selected to be representative of each major crop-soil class. Accuracies in each case, on a total acreage basis, were greater than 90 percent.

Classification and soil moisture determination of agricultural fields

NASA Technical Reports Server (NTRS)

Vandenbroek, A. C.; Groot, J. S.

1993-01-01

During the Mac-Europe campaign of 1991 several SAR (Synthetic Aperature Radar) experiments were carried out in the Flevoland test area in the Netherlands. The test site consists of a forested and an agricultural area with more than 15 different crop types. The experiments took place in June and July (mid to late growing season). The area was monitored by the spaceborne C-band VV polarized ERS-1, the Dutch airborne PHARS with similar frequency and polarization and the three-frequency PP-, L-, and C-band) polarimetric AIRSAR system of NASA/JPL. The last system passed over on June 15, 3, 12, and 28. The last two dates coincided with the overpasses of the PHARS and the ERS-1. Comparison of the results showed that backscattering coefficients from the three systems agree quite well. In this paper we present the results of a study of crop type classification (section 2) and soil moisture determination in the agricultural area (section 3). For these studies we used field averaged Stokes matrices extracted from the AIRSAR data (processor version 3.55 or 3.56).

Developments and departures in the philosophy of soil science

USDA-ARS?s Scientific Manuscript database

Traditional soil science curriculums provide comprehensive instruction on soil properties, soil classification, and the physical, chemical, and biological processes that occur in soils. This reductionist perspective is sometimes balanced with a more holistic perspective that focuses on soils as natu...

Site classification for northern forest species

Treesearch

Willard H. Carmean

1977-01-01

Summarizes the extensive literature for northern forest species covering site index curves, site index species comparisons, growth intercepts, soil-site studies, plant indicators, physiographic site classifications, and soil survey studies. The advantages and disadvantages of each are discussed, and suggestions are made for future research using each of these methods....

7 CFR 658.5 - Criteria.

Code of Federal Regulations, 2011 CFR

2011-01-01

... information from several sources including national cooperative soil surveys or other acceptable soil surveys, NRCS field office technical guides, soil potential ratings or soil productivity ratings, land capability classifications, and important farmland determinations. Based on this information, groups of soils...

7 CFR 658.5 - Criteria.

Code of Federal Regulations, 2010 CFR

2010-01-01

... information from several sources including national cooperative soil surveys or other acceptable soil surveys, NRCS field office technical guides, soil potential ratings or soil productivity ratings, land capability classifications, and important farmland determinations. Based on this information, groups of soils...

Estimating of Soil Texture Using Landsat Imagery: a Case Study in Thatta Tehsil, Sindh

NASA Astrophysics Data System (ADS)

Khalil, Zahid

2016-07-01

Soil texture is considered as an important environment factor for agricultural growth. It is the most essential part for soil classification in large scale. Today the precise soil information in large scale is of great demand from various stakeholders including soil scientists, environmental managers, land use planners and traditional agricultural users. With the increasing demand of soil properties in fine scale spatial resolution made the traditional laboratory methods inadequate. In addition the costs of soil analysis with precision agriculture systems are more expensive than traditional methods. In this regard, the application of geo-spatial techniques can be used as an alternative for examining soil analysis. This study aims to examine the ability of Geo-spatial techniques in identifying the spatial patterns of soil attributes in fine scale. Around 28 samples of soil were collected from the different areas of Thatta Tehsil, Sindh, Pakistan for analyzing soil texture. An Ordinary Least Square (OLS) regression analysis was used to relate the reflectance values of Landsat8 OLI imagery with the soil variables. The analysis showed there was a significant relationship (p<0.05) of band 2 and 5 with silt% (R2 = 0.52), and band 4 and 6 with clay% (R2 =0.40). The equation derived from OLS analysis was then used for the whole study area for deriving soil attributes. The USDA textural classification triangle was implementing for the derivation of soil texture map in GIS environment. The outcome revealed that the 'sandy loam' was in great quantity followed by loam, sandy clay loam and clay loam. The outcome shows that the Geo-spatial techniques could be used efficiently for mapping soil texture of a larger area in fine scale. This technology helped in decreasing cost, time and increase detailed information by reducing field work to a considerable level.

Relationship between the erosion properties of soils and other parameters

USDA-ARS?s Scientific Manuscript database

Soil parameters are essential for erosion process prediction and ultimately improved model development, especially as they relate to dam and levee failure. Soil parameters including soil texture and structure, soil classification, soil compaction, moisture content, and degree of saturation can play...

A simulation of Earthquake Loss Estimation in Southeastern Korea using HAZUS and the local site classification Map

NASA Astrophysics Data System (ADS)

Kang, S.; Kim, K.

2013-12-01

Regionally varying seismic hazards can be estimated using an earthquake loss estimation system (e.g. HAZUS-MH). The estimations for actual earthquakes help federal and local authorities develop rapid, effective recovery measures. Estimates for scenario earthquakes help in designing a comprehensive earthquake hazard mitigation plan. Local site characteristics influence the ground motion. Although direct measurements are desirable to construct a site-amplification map, such data are expensive and time consuming to collect. Thus we derived a site classification map of the southern Korean Peninsula using geologic and geomorphologic data, which are readily available for the entire southern Korean Peninsula. Class B sites (mainly rock) are predominant in the area, although localized areas of softer soils are found along major rivers and seashores. The site classification map is compared with independent site classification studies to confirm our site classification map effectively represents the local behavior of site amplification during an earthquake. We then estimated the losses due to a magnitude 6.7 scenario earthquake in Gyeongju, southeastern Korea, with and without the site classification map. Significant differences in loss estimates were observed. The loss without the site classification map decreased without variation with increasing epicentral distance, while the loss with the site classification map varied from region to region, due to both the epicentral distance and local site effects. The major cause of the large loss expected in Gyeongju is the short epicentral distance. Pohang Nam-Gu is located farther from the earthquake source region. Nonetheless, the loss estimates in the remote city are as large as those in Gyeongju and are attributed to the site effect of soft soil found widely in the area.

Confirmation of Two Undescribed Fungal Species from Dokdo of Korea Based on Current Classification System Using Multi Loci

PubMed Central

Lee, Hye Won; Nguyen, Thi Thuong Thuong; Mun, Hye Yeon; Lee, Haengsub; Kim, Changmu

2015-01-01

Using dilution plating method, 47 fungal isolates were obtained from a soil sample collected from Dokdo in the East Sea of Korea in 2013. In this study, two fungal isolates, EML-MFS30-1 and EML-DDSF4, were confirmed as undescribed species, Metarhizium guizhouense and Mortierella oligospora in Korea based on current classification system using multi loci including rDNA internal transcribed spacer, large subunit, small subunit, and β-tubulin (BTUB) genes. Herein, detailed morphological descriptions on characters of the undescribed fungal species as well as their molecular phylogenetic status are provided with comparisons to related species. PMID:26839498

Classification and Use of Natural and Anthropogenic Soils by Indigenous Communities of the Upper Amazon Region of Colombia.

PubMed

Peña-Venegas, C P; Stomph, T J; Verschoor, G; Echeverri, J A; Struik, P C

Outsiders often oversimplify Amazon soil use by assuming that abundantly available natural soils are poorly suited to agriculture and that sporadic anthropogenic soils are agriculturally productive. Local perceptions about the potentials and limitations of soils probably differ, but information on these perceptions is scarce. We therefore examined how four indigenous communities in the Middle Caquetá River region in the Colombian Amazon classify and use natural and anthropogenic soils. The study was framed in ethnopedology: local classifications, preferences, rankings, and soil uses were recorded through interviews and field observations. These communities recognized nine soils varying in suitability for agriculture. They identified anthropogenic soils as most suitable for agriculture, but only one group used them predominantly for their swiddens. As these communities did not perceive soil nutrient status as limiting, they did not base crop-site selection on soil fertility or on the interplay between soil quality and performance of manioc genetic resources.

Soil Management Plan for the Oak Ridge Y-12 National Security Complex Oak Ridge, Tennessee

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

2005-03-02

This Soil Management Plan applies to all activities conducted under the auspices of the National Nuclear Security Administration (NNSA) Oak Ridge Y-12 National Security Complex (Y-12) that involve soil disturbance and potential management of waste soil. The plan was prepared under the direction of the Y-12 Environmental Compliance Department of the Environment, Safety, and Health Division. Soil disturbances related to maintenance activities, utility and building construction projects, or demolition projects fall within the purview of the plan. This Soil Management Plan represents an integrated, visually oriented, planning and information resource tool for decision making involving excavation or disturbance of soilmore » at Y-12. This Soil Management Plan addresses three primary elements. (1) Regulatory and programmatic requirements for management of soil based on the location of a soil disturbance project and/or the regulatory classification of any contaminants that may be present (Chap. 2). Five general regulatory or programmatic classifications of soil are recognized to be potentially present at Y-12; soil may fall under one or more these classifications: (a) Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) pursuant to the Oak Ridge Reservation (ORR) Federal Facilities Agreement; (b) Resource Conservation and Recovery Act (RCRA); (c) RCRA 3004(u) solid waste managements units pursuant to the RCRA Hazardous and Solid Waste Amendments Act of 1984 permit for the ORR; (d) Toxic Substances and Control Act-regulated soil containing polychlorinated biphenyls; and (e) Radiologically contaminated soil regulated under the Atomic Energy Act review process. (2) Information for project planners on current and future planned remedial actions (RAs), as prescribed by CERCLA decision documents (including the scope of the actions and remedial goals), land use controls implemented to support or maintain RAs, RCRA post-closure regulatory requirements for former waste management units, legacy contamination source areas and distribution of contamination in soils, and environmental infrastructure (e.g., caps, monitoring systems, etc.) that is in place or planned in association with RAs. (3) Regulatory considerations and processes for management and disposition of waste soil upon generation, including regulatory drivers, best management practices (BMPs), waste determination protocols, waste acceptance criteria, and existing waste management procedures and BMPs for Y-12. This Soil Management Plan provides information to project planners to better coordinate their activities with other organizations and programs with a vested interest in soil disturbance activities at Y-12. The information allows project managers and maintenance personnel to evaluate and anticipate potential contaminant levels that may be present at a proposed soil disturbance site prior to commencement of activities and allows a more accurate assessment of potential waste management requirements.« less

EXTENDING AQUATIC CLASSIFICATION TO THE LANDSCAPE SCALE HYDROLOGY-BASED STRATEGIES

EPA Science Inventory

Aquatic classification of single water bodies (lakes, wetlands, estuaries) is often based on geologic origin, while stream classification has relied on multiple factors related to landform, geomorphology, and soils. We have developed an approach to aquatic classification based o...

Do We Need a New Definition of Soil?

NASA Astrophysics Data System (ADS)

Arnold, Richard W.; Brevik, Eric C.

2014-05-01

Effective communication is really desirable to better relate with politicians, an interested lay public, and others not involved in soil science. Soil survey programs are intended to help people understand how soils function in their landscapes to make ecosystems operate better without damaging the environment and to indicate different kinds of suitability for various purposes. The properties of soils as recognized, described, and mapped at detailed scales form the basis for developing diagnostics for a systematic taxonomy that enables scientists to interact with other. In the USA mapping done at scales of 1:15,840± made it possible to define and use so-called "soil series", initially as soil map units, but later as central concepts of a set of soils which could be segregated using phases to indicate important features, primarily for farming. Detailed soil surveys published using a standard format helps maintain uniformity across the country. Soil series are recognized as the basic units of soils within the evolving hierarchical soil taxonomy and diagnostic properties are defined, measured and used to update and modify the scientific classification. Concepts like soil quality and soil function are considered to be "attributes" and not basic properties of soils. They are the collective interpretation of the combination of properties thought to be relevant for communicating important aspects of using, managing, restoring, and protecting the lands of any locality, region, or country. A famous example in the US was the land capability system with classes and subclasses of suitability for agricultural land uses. An updated soil survey in California contains over 500 pages providing details about classes of 30 different functional soil classifications for 155 map units. Over the years soil extension agents were the interpreters of the science to the lay folks and could help them form mental pictures of soils and soil landscapes locally They were the early leaders of what we think of as "field guides to natural resources" such as trees, flowers, birds, and so forth. There were not such books to identify soils but the basics have always been there waiting for proper attention, preparation, and use. At smaller scales the map units are always combinations of the basic units, and now it is possible to use some higher category classes to indicate the central concepts of larger areas. Every year soil scientists around the world observe and describe features and properties of soils in landscapes that are getting more attention than previously. Soil genesis studies help us to better understand the complexity of landscape and soil evolution. Often they indicate that current soils are commonly being formed from parts of previous soils. We do not need a new definition of soil. We do need to work on developing and testing complete interpretive classifications of soils to better meet the needs of societies today. This means "soil quality", "soil functions", and other attributes of soils require more attention, now and in the near future to permit politicians and lay publics to better understand the significance of soils to the future of civilization. "After all is said and done, more is said than done" Aesop, Greek storyteller

Traditional knowledge among Zapotecs of Sierra Madre Del Sur, Oaxaca. Does it represent a base for plant resources management and conservation?

PubMed

Luna-José, Azucena de Lourdes; Aguilar, Beatriz Rendón

2012-07-12

Traditional classification systems represent cognitive processes of human cultures in the world. It synthesizes specific conceptions of nature, as well as cumulative learning, beliefs and customs that are part of a particular human community or society. Traditional knowledge has been analyzed from different viewpoints, one of which corresponds to the analysis of ethnoclassifications. In this work, a brief analysis of the botanical traditional knowledge among Zapotecs of the municipality of San Agustin Loxicha, Oaxaca was conducted. The purposes of this study were: a) to analyze the traditional ecological knowledge of local plant resources through the folk classification of both landscapes and plants and b) to determine the role that this knowledge has played in plant resource management and conservation. The study was developed in five communities of San Agustín Loxicha. From field trips, plant specimens were collected and showed to local people in order to get the Spanish or Zapotec names; through interviews with local people, we obtained names and identified classification categories of plants, vegetation units, and soil types. We found a logic structure in Zapotec plant names, based on linguistic terms, as well as morphological and ecological caracteristics. We followed the classification principles proposed by Berlin [6] in order to build a hierarchical structure of life forms, names and other characteristics mentioned by people. We recorded 757 plant names. Most of them (67%) have an equivalent Zapotec name and the remaining 33% had mixed names with Zapotec and Spanish terms. Plants were categorized as native plants, plants introduced in pre-Hispanic times, or plants introduced later. All of them are grouped in a hierarchical classification, which include life form, generic, specific, and varietal categories. Monotypic and polytypic names are used to further classify plants. This holistic classification system plays an important role for local people in many aspects: it helps to organize and make sense of the diversity, to understand the interrelation among plants-soil-vegetation and to classify their physical space since they relate plants with a particular vegetation unit and a kind of soil. The locals also make a rational use of these elements, because they know which crops can grow in any vegetation unit, or which places are indicated to recollect plants. These aspects are interconnected and could be fundamental for a rational use and management of plant resources.

Land cover heterogeneity and soil respiration in a west Greenland tundra landscape

NASA Astrophysics Data System (ADS)

Bradley-Cook, J. I.; Burzynski, A.; Hammond, C. R.; Virginia, R. A.

2011-12-01

Multiple direct and indirect pathways underlie the association between land cover classification, temperature and soil respiration. Temperature is a main control of the biological processes that constitute soil respiration, yet the effect of changing atmospheric temperatures on soil carbon flux is unresolved. This study examines associations amongst land cover, soil carbon characteristics, soil respiration, and temperature in an Arctic tundra landscape in western Greenland. We used a 1.34 meter resolution multi-spectral WorldView2 satellite image to conduct an unsupervised multi-staged ISODATA classification to characterize land cover heterogeneity. The four band image was taken on July 10th, 2010, and captures an 18 km by 15 km area in the vicinity of Kangerlussuaq. The four major terrestrial land cover classes identified were: shrub-dominated, graminoid-dominated, mixed vegetation, and bare soil. The bare soil class was comprised of patches where surface soil has been deflated by wind and ridge-top fellfield. We hypothesize that soil respiration and soil carbon storage are associated with land cover classification and temperature. We set up a hierarchical field sampling design to directly observe spatial variation between and within land cover classes along a 20 km temperature gradient extending west from Russell Glacier on the margin of the Greenland Ice Sheet. We used the land cover classification map and ground verification to select nine sites, each containing patches of the four land cover classes. Within each patch we collected soil samples from a 50 cm pit, quantified vegetation, measured active layer depth and determined landscape characteristics. From a subset of field sites we collected additional 10 cm surface soil samples to estimate soil heterogeneity within patches and measured soil respiration using a LiCor 8100 Infrared Gas Analyzer. Soil respiration rates varied with land cover classes, with values ranging from 0.2 mg C/m^2/hr in the bare soil class to over 5 mg C/m^2/hr in the graminoid-dominated class. These findings suggest that shifts in land cover vegetation types, especially soil and vegetation loss (e.g. from wind deflation), can alter landscape soil respiration. We relate soil respiration measurements to soil, vegetation, and permafrost characteristics to understand how ecosystem properties and processes vary at the landscape scale. A long-term goal of this research is to develop a spatially explicit model of soil organic matter, soil respiration, and temperature sensitivity of soil carbon dynamics for a western Greenland permafrost tundra ecosystems.

Acidity field of soils as ion-exchange systems and the diagnostics of genetic soil horizons

NASA Astrophysics Data System (ADS)

Kokotov, Yu. A.; Sukhacheva, E. Yu.; Aparin, B. F.

2014-12-01

For the comprehensive description of the acidity of a two-phase ion-exchange system, we should analyze two curves of the ionite titration by a strong base in water and salt solutions and find the quantitative relationships between the corresponding pH characteristics. An idea of the three-dimensional field of acidity of ion-exchange systems (the phase space of the soil acidity characteristics) and its three two-dimensional projections is suggested. For soils, three interrelated characteristics—the pH values of the salt and water extracts and the degree of base saturation—can serve as spatial coordinates for the acidity field. Representation of factual data in this field makes it possible to compare and analyze the acidity characteristics of different soils and soil horizons and to determine their specific features. Differentiation of the field into separate volumes allows one to present the data in a discrete form. We have studied the distribution patterns of the groups of soil horizons from Leningrad oblast and other regions of northwestern Russia in the acidity field. The studied samples are grouped in different partially overlapping areas of the projections of the acidity field. The results of this grouping attest to the correctness of the modern classification of Russian soils. A notion of the characteristic soil area in the acidity field is suggested; it can be applied to all the soils with a leaching soil water regime.

Automated Coastal Engineering System: Technical Reference

DTIC Science & Technology

1992-09-01

of Contents ACES Technical Reference Wave Transmission Through Permeable Structures ..................................... 5-4 Littoral Processes...A-2 Table A-4: Grain-Size Scales ( Soil Classification) ..................................... A-3 Table A-5: Major Tidal Constituents... Permeable Structures Lonphore Sediment Tranaport Littoral Numerical Si~ulation of Time-Dependent Beach and Dune Erosion Processes Calculation of Composite

A regional perspective of the physiographic provinces of the southeastern United States

Treesearch

James H. Miller; K.S. Robinson

1995-01-01

Abstract.  A landscape classification system using defined units for physiography, landform, and soils is needed to organize ecological information and to serve as an aid for landscape management.  To assist in this effort a composite physiographic map is presented to 12 southeastern states.

Comparison of different landform classification methods for digital landform and soil mapping of the Iranian loess plateau

NASA Astrophysics Data System (ADS)

Hoffmeister, Dirk; Kramm, Tanja; Curdt, Constanze; Maleki, Sedigheh; Khormali, Farhad; Kehl, Martin

2016-04-01

The Iranian loess plateau is covered by loess deposits, up to 70 m thick. Tectonic uplift triggered deep erosion and valley incision into the loess and underlying marine deposits. Soil development strongly relates to the aspect of these incised slopes, because on northern slopes vegetation protects the soil surface against erosion and facilitates formation and preservation of a Cambisol, whereas on south-facing slopes soils were probably eroded and weakly developed Entisols formed. While the whole area is intensively stocked with sheep and goat, rain-fed cropping of winter wheat is practiced on the valley floors. Most time of the year, the soil surface is unprotected against rainfall, which is one of the factors promoting soil erosion and serious flooding. However, little information is available on soil distribution, plant cover and the geomorphological evolution of the plateau, as well as on potentials and problems in land use. Thus, digital landform and soil mapping is needed. As a requirement of digital landform and soil mapping, four different landform classification methods were compared and evaluated. These geomorphometric classifications were run on two different scales. On the whole area an ASTER GDEM and SRTM dataset (30 m pixel resolution) was used. Likewise, two high-resolution digital elevation models were derived from Pléiades satellite stereo-imagery (< 1m pixel resolution, 10 by 10 km). The high-resolution information of this dataset was aggregated to datasets of 5 and 10 m scale. The applied classification methods are the Geomorphons approach, an object-based image approach, the topographical position index and a mainly slope based approach. The accuracy of the classification was checked with a location related image dataset obtained in a field survey (n ~ 150) in September 2015. The accuracy of the DEMs was compared to measured DGPS trenches and map-based elevation data. The overall derived accuracy of the landform classification based on the high-resolution DEM with a resolution of 5 m is approximately 70% and on a 10 m resolution >58%. For the 30 m resolution datasets is the achieved accuracy approximately 40%, as several small scale features are not recognizable in this resolution. Thus, for an accurate differentiation between different important landform types, high-resolution datasets are necessary for this strongly shaped area. One major problem of this approach are the different classes derived by each method and the various class annotations. The result of this evaluation will be regarded for the derivation of landform and soil maps.

Hygrothermal Material Properties for Soils in Building Science

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kehrer, Manfred; Pallin, Simon B.

2017-01-01

Hygrothermal performance of soils coupled to buildings is complicated because of the dearth of information on soil properties. However they are important when numerical simulation of coupled heat and moisture transport for below-grade building components are performed as their temperature and moisture content has an influence on the durability of the below-grade building component. Soils can be classified by soil texture. According to the Unified Soil Classification System (USCA), 12 different soils can be defined on the basis of three soil components: clay, sand, and silt. This study shows how existing material properties for typical American soils can be transferredmore » and used for the calculation of the coupled heat and moisture transport of building components in contact with soil. Furthermore a thermal validation with field measurements under known boundary conditions is part of this study, too. Field measurements for soil temperature and moisture content for two specified soils are carried out right now under known boundary conditions. As these field measurements are not finished yet, the full hygrothermal validation is still missing« less

Estimating Soil Organic Carbon Stocks and Spatial Patterns with Statistical and GIS-Based Methods

PubMed Central

Zhi, Junjun; Jing, Changwei; Lin, Shengpan; Zhang, Cao; Liu, Qiankun; DeGloria, Stephen D.; Wu, Jiaping

2014-01-01

Accurately quantifying soil organic carbon (SOC) is considered fundamental to studying soil quality, modeling the global carbon cycle, and assessing global climate change. This study evaluated the uncertainties caused by up-scaling of soil properties from the county scale to the provincial scale and from lower-level classification of Soil Species to Soil Group, using four methods: the mean, median, Soil Profile Statistics (SPS), and pedological professional knowledge based (PKB) methods. For the SPS method, SOC stock is calculated at the county scale by multiplying the mean SOC density value of each soil type in a county by its corresponding area. For the mean or median method, SOC density value of each soil type is calculated using provincial arithmetic mean or median. For the PKB method, SOC density value of each soil type is calculated at the county scale considering soil parent materials and spatial locations of all soil profiles. A newly constructed 1∶50,000 soil survey geographic database of Zhejiang Province, China, was used for evaluation. Results indicated that with soil classification levels up-scaling from Soil Species to Soil Group, the variation of estimated SOC stocks among different soil classification levels was obviously lower than that among different methods. The difference in the estimated SOC stocks among the four methods was lowest at the Soil Species level. The differences in SOC stocks among the mean, median, and PKB methods for different Soil Groups resulted from the differences in the procedure of aggregating soil profile properties to represent the attributes of one soil type. Compared with the other three estimation methods (i.e., the SPS, mean and median methods), the PKB method holds significant promise for characterizing spatial differences in SOC distribution because spatial locations of all soil profiles are considered during the aggregation procedure. PMID:24840890

A surface fuel classification for estimating fire effects

Treesearch

Duncan C. Lutes; Robert E. Keane; John F. Caratti

2009-01-01

We present a classification of duff, litter, fine woody debris, and logs that can be used to stratify a project area into sites with fuel loading that yield significantly different emissions and maximum soil surface temperature. Total particulate matter smaller than 2.5?m in diameter and maximum soil surface temperature were simulated using the First...

Predicting and quantifying soil processes using “geomorphon” landform Classification

USDA-ARS?s Scientific Manuscript database

Soil development and behavior vary spatially at multiple observation scales. Predicting and quantifying soil properties and processes via a catena integrates predictable landscape scale variation relevant to both management decisions and soil survey. Soil maps generally convey variation as a set of ...

Soil texture classification algorithm using RGB characteristics of soil images

USDA-ARS?s Scientific Manuscript database

Soil texture has an important influence on agriculture, affecting crop selection, movement of nutrients and water, soil electrical conductivity, and crop growth. Soil texture has traditionally been determined in the laboratory using pipette and hydrometer methods that require a considerable amount o...

Ch'ol nomenclature for soil classification in the ejido Oxolotán, Tacotalpa, Tabasco, México.

PubMed

Sánchez-Hernández, Rufo; Méndez-De la Cruz, Lucero; Palma-López, David J; Bautista-Zuñiga, Francisco

2018-05-30

The traditional ecological knowledge of land of the Ch'ol originary people from southeast Mexico forms part of their cultural identity; it is local and holistic and implies an integrated physical and spiritual worldview that contributes to improve their living conditions. We analyzed the nomenclature for soil classification used in the Mexican state of Tabasco by the Ch'ol farmers with the objective of contributing to the knowledge of the Maya soil classification. A map of the study area was generated from the digital database of parcels in the ejido Oxolotán in the municipality of Tacotalpa, to which a geopedological map was overlaid in order to obtain modeled topographic profiles (Zavala-Cruz et al., Ecosistemas y Recursos Agropecuarios 3:161-171, 2016). In each modeled profile, a soil profile was made and classified according to IUSS Working Group WRB (181, 2014) in order to generate a map of soil groups, which was used to survey the study area with the participation of 245 local Ch'ol farmers for establishing an ethnopedological soil classification (Ortiz et al.: 62, 1990). In addition, we organized a participatory workshop with 35 people to know details of the names of the soils and their indicators of fertility and workability, from which we selected 15 participants for field trips and description of soil profiles. The color, texture, and stoniness are attributes important in the Ch'ol nomenclature, although the names do not completely reflect the visible characteristic of the soil surface. On the other hand, the mere presence of stones is sufficient to name a land class, while according to IUSS Working Group WRB (181, 2014), a certain amount and distribution of stones in the soil profiles is necessary to be taken into consideration in the name. Perception of soil quality by local farmers considers the compaction or hardness of the cultivable soil layer, because of which black or sandy soils are perceived as better for cultivation of banana, or as secondary vegetation in fallow. Red, yellow, or brown soils are seen as of less quality and are only used for establishing grasslands, while maize is cultivated in all soil classes. Farmers provided the Ch'ol nomenclature, perceived problems, and uses of each class of soil. Translation of Ch'ol soil names and comparison with descriptions of soil profiles revealed that the Ch'ol soil nomenclature takes into account the soil profile, given it is based on characteristics of both surface and subsurface horizons including color of soil matrix and mottles, stoniness, texture, and vegetation.

Land use survey and mapping and water resources investigation in Korea

NASA Technical Reports Server (NTRS)

Choi, J. H.; Kim, W. I.; Son, D. S. (Principal Investigator)

1978-01-01

The author has identified the following significant results. Land use imagery is applicable to land use classification for small scale land use mapping less than 1:250,000. Land use mapping by satellite is more efficient and more cost-effective than land use mapping from conventional medium altitude aerial photographs. Six categories of level 1 land use classification are recognizable from MSS imagery. A hydrogeomorphological study of the Han River basin indicates that band 7 is useful for recognizing the soil and the weathering part of bed rock. The morphological change of the main river is accurately recognized and the drainage system in the area observed is easily classified because of the more or less simple rock type. Although the direct hydrological characteristics are not obtained from the MSS imagery, the indirect information such as the permeability of the soil and the vegetation cover, is helpful in interpreting the hydrological aspects.

Multisensor fusion remote sensing technology for assessing multitemporal responses in ecohydrological systems

NASA Astrophysics Data System (ADS)

Makkeasorn, Ammarin

This study aims at presenting a systematic soil moisture estimation method for the Choke Canyon Reservoir Watershed (CCRW), a semiarid watershed with an area of over 14,200 km2 in south Texas. With the aid of five corner reflectors, the RADARSAT-1 Synthetic Aperture Radar (SAR) imageries of the study area acquired in April and September 2004 were processed by both radiometric and geometric calibrations at first. New soil moisture estimation models derived by genetic programming (GP) technique were then developed and applied to support the soil moisture distribution analysis. The GP-based nonlinear function derived in the evolutionary process uniquely links a series of crucial topographic and geographic features. Included in this process are slope, aspect, vegetation cover, and soil permeability to compliment the well-calibrated SAR data. Research indicates that the novel application of GP proved useful for generating a highly nonlinear structure in regression regime, which exhibits very strong correlations statistically between the model estimates and the ground truth measurements (volumetric water content) on the basis of the unseen data sets. In an effort to produce the soil moisture distributions over seasons, it eventually leads to characterizing local- to regional-scale soil moisture variability and performing the possible estimation of water storages of the terrestrial hydrosphere. A new evolutionary computational, supervised classification scheme ( Riparian Classification Algorithm, RICAL) was developed and used to identify the change of riparian zones in a semi-arid watershed temporally and spatially. The case study uniquely demonstrates an effort to incorporating both vegetation index and soil moisture estimates based on Landsat 5 TM and RADARSAT-1 imageries while trying to improve the riparian classification in the Choke Canyon Reservoir Watershed (CCRW), South Texas. The estimation of soil moisture based on RADARSAT-1 Synthetic Aperture Radar (SAR) satellite imagery as previously developed was used. Eight commonly used vegetation indices were calculated from the reflectance obtained from Landsat 5 TM satellite images. The vegetation indices were individually used to classify vegetation cover in association with genetic programming algorithm. The soil moisture and vegetation indices were integrated into Landsat TM images based on a pre-pixel channel approach for riparian classification. Two different classification algorithms were used including genetic programming, and a combination of ISODATA and maximum likelihood supervised classification. The white box feature of genetic programming revealed the comparative advantage of all input parameters. The GP algorithm yielded more than 90% accuracy, based on unseen ground data, using vegetation index and Landsat reflectance band 1, 2, 3, and 4. The detection of changes in the buffer zone was proved to be technically feasible with high accuracy. Overall, the development of the RICAL algorithm may lead to the formulation of more effective management strategies for the handling of non-point source pollution control, bird habitat monitoring, and grazing and live stock management in the future. Geo-environmental information amassed in this study includes soil permeability, surface temperature, soil moisture, precipitation, leaf area index (LAI) and normalized difference vegetation index (NDVI). With the aid of a remote sensing-based GIP analysis, only five locations out of more than 800 candidate sites were selected by the spatial analysis, and then confirmed by a field investigation. The methodology developed in this remote sensing-based GIP analysis will significantly advance the state-of-the-art technology in optimum arrangement/distribution of water sensor platforms for maximum sensing coverage and information-extraction capacity. To more efficiently use the limited amount of water or to resourcefully provide adequate time for flood warning, the results have led us to seek advanced techniques for improving streamflow forecasting. The objective of this section of research is to incorporate sea surface temperature (SST), Next Generation Radar (NEXRAD) and meteorological characteristics with historical stream data to forecast the actual streamflow using genetic programming. This study case concerns the forecasting of stream discharge of a complex-terrain, semi-arid watershed. This study elicits microclimatological factors and the resultant stream flow rate in river system given the influence of dynamic basin features such as soil moisture, soil temperature, ambient relative humidity, air temperature, sea surface temperature, and precipitation. Evaluations of the forecasting results are expressed in terms of the percentage error (PE), the root-mean-square error (RMSE), and the square of the Pearson product moment correlation coefficient (r-squared value). The developed models can predict streamflow with very good accuracy with an r-square of 0.84 and PE of 1% for a 30-day prediction. (Abstract shortened by UMI.)

Turning soil survey data into digital soil maps in the Energy Region Eger Research Model Area

NASA Astrophysics Data System (ADS)

Pásztor, László; Dobos, Anna; Kürti, Lívia; Takács, Katalin; Laborczi, Annamária

2015-04-01

Agria-Innoregion Knowledge Centre of the Eszterházy Károly College has carried out targeted basic researches in the field of renewable energy sources and climate change in the framework of TÁMOP-4.2.2.A-11/1/KONV project. The project has covered certain issues, which require the specific knowledge of the soil cover; for example: (i) investigation of quantitative and qualitative characteristics of natural and landscape resources; (ii) determination of local amount and characteristics of renewable energy sources; (iii) natural/environmental risk analysis by surveying the risk factors. The Energy Region Eger Research Model Area consists of 23 villages and is located in North-Hungary, at the Western part of Bükkalja. Bükkalja is a pediment surface with erosional valleys and dense river network. The diverse morphology of this area results diversity in soil types and soil properties as well. There was large-scale (1:10,000 and 1:25,000 scale) soil mappings in this area in the 1960's and 1970's which provided soil maps, but with reduced spatial coverage and not with fully functional thematics. To achive the recent tasks (like planning suitable/optimal land-use system, estimating biomass production and development of agricultural and ecomonic systems in terms of sustainable regional development) new survey was planned and carried out by the staff of the College. To map the soils in the study area 10 to 22 soil profiles were uncovered per settlement in 2013 and 2014. Field work was carried out according to the FAO Guidelines for Soil Description and WRB soil classification system was used for naming soils. According to the general goal of soil mapping the survey data had to be spatially extended to regionalize the collected thematic local knowledge related to soil cover. Firstly three thematic maps were compiled by digital soil mapping methods: thickness of topsoil, genetic soil type and rate of surface erosion. High resolution digital elevation model, Earth observation imagery, geology and land cover maps were used as spatial ancillary environmental variables related to soil forming processes. Regression kriging (RK) has been used for the spatial inference of quantitative data (thickness of topsoil); classification and regression trees (CART) were applied for the spatial inference of category type information (genetic soil type and rate of surface erosion) with the aid of the available and properly preprocessed auxiliary co-variables. The applied spatial resolution was 25 meters. The deduced digital soil maps hopefully will significantly promote to plan sustainable economic model in the region which can provide protection and regeneration of local natural conditions and potentials for local inhabitants for a long time. Acknowledgement: Our work was supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167) and TÁMOP-4.2.2.A-11/1/KONV project.

Random whole metagenomic sequencing for forensic discrimination of soils.

PubMed

Khodakova, Anastasia S; Smith, Renee J; Burgoyne, Leigh; Abarno, Damien; Linacre, Adrian

2014-01-01

Here we assess the ability of random whole metagenomic sequencing approaches to discriminate between similar soils from two geographically distinct urban sites for application in forensic science. Repeat samples from two parklands in residential areas separated by approximately 3 km were collected and the DNA was extracted. Shotgun, whole genome amplification (WGA) and single arbitrarily primed DNA amplification (AP-PCR) based sequencing techniques were then used to generate soil metagenomic profiles. Full and subsampled metagenomic datasets were then annotated against M5NR/M5RNA (taxonomic classification) and SEED Subsystems (metabolic classification) databases. Further comparative analyses were performed using a number of statistical tools including: hierarchical agglomerative clustering (CLUSTER); similarity profile analysis (SIMPROF); non-metric multidimensional scaling (NMDS); and canonical analysis of principal coordinates (CAP) at all major levels of taxonomic and metabolic classification. Our data showed that shotgun and WGA-based approaches generated highly similar metagenomic profiles for the soil samples such that the soil samples could not be distinguished accurately. An AP-PCR based approach was shown to be successful at obtaining reproducible site-specific metagenomic DNA profiles, which in turn were employed for successful discrimination of visually similar soil samples collected from two different locations.

A study of the utilization of ERTS-1 data from the Wabash River Basin. [soil mapping, crop identification, water resources

NASA Technical Reports Server (NTRS)

Landgrebe, D. A. (Principal Investigator)

1973-01-01

The author has identified the following significant results. In soil association mapping, computerized analysis of ERTS-1 MSS data has yielded images which will prove useful in the ongoing Cooperative Soil Survey program, involving the Soil Conservation Service of USDA and other state and local agencies. In the present mode of operation, a soil survey for a county may take up to 5 years to be completed. Results indicate that a great deal of soils information can be extracted from ERTS-1 data by computer analysis. This information is expected to be very valuable in the premapping conference phase of a soil survey, resulting in more efficient field operations during the actual mapping. In the earth surface features mapping effort it was found that temporal data improved the classification accuracy of forest classification in Tippecanoe County, Indiana. In water resources study a severe scanner look angle effect was observed in the aircraft scanner data of a test lake which was not present in ERTS-1 data of the same site. This effect was greatly accentuated by surface roughness caused by strong winds. Quantitative evaluation of urban features classification in ERTS-1 data was obtained. An 87.1% test accuracy was obtained for eight categories in Marion County, Indiana.

The effect of finite field size on classification and atmospheric correction

NASA Technical Reports Server (NTRS)

Kaufman, Y. J.; Fraser, R. S.

1981-01-01

The atmospheric effect on the upward radiance of sunlight scattered from the Earth-atmosphere system is strongly influenced by the contrasts between fields and their sizes. For a given atmospheric turbidity, the atmospheric effect on classification of surface features is much stronger for nonuniform surfaces than for uniform surfaces. Therefore, the classification accuracy of agricultural fields and urban areas is dependent not only on the optical characteristics of the atmosphere, but also on the size of the surface do not account for the nonuniformity of the surface have only a slight effect on the classification accuracy; in other cases the classification accuracy descreases. The radiances above finite fields were computed to simulate radiances measured by a satellite. A simulation case including 11 agricultural fields and four natural fields (water, soil, savanah, and forest) was used to test the effect of the size of the background reflectance and the optical thickness of the atmosphere on classification accuracy. It is concluded that new atmospheric correction methods, which take into account the finite size of the fields, have to be developed to improve significantly the classification accuracy.

Site Classification using Multichannel Channel Analysis of Surface Wave (MASW) method on Soft and Hard Ground

NASA Astrophysics Data System (ADS)

Ashraf, M. A. M.; Kumar, N. S.; Yusoh, R.; Hazreek, Z. A. M.; Aziman, M.

2018-04-01

Site classification utilizing average shear wave velocity (Vs(30) up to 30 meters depth is a typical parameter. Numerous geophysical methods have been proposed for estimation of shear wave velocity by utilizing assortment of testing configuration, processing method, and inversion algorithm. Multichannel Analysis of Surface Wave (MASW) method is been rehearsed by numerous specialist and professional to geotechnical engineering for local site characterization and classification. This study aims to determine the site classification on soft and hard ground using MASW method. The subsurface classification was made utilizing National Earthquake Hazards Reduction Program (NERHP) and international Building Code (IBC) classification. Two sites are chosen to acquire the shear wave velocity which is in the state of Pulau Pinang for soft soil and Perlis for hard rock. Results recommend that MASW technique can be utilized to spatially calculate the distribution of shear wave velocity (Vs(30)) in soil and rock to characterize areas.

Soil Testing as a Classroom Exercise to Determine Soil-forming Processes and Soil Classification.

ERIC Educational Resources Information Center

Bencloski, Joseph W.

1980-01-01

Describes a learning activity involving correctly matching soils with environments. The activity is intended for use in college level physical geography courses. Information is presented on instructional objectives, outline of preparatory lectures, soil test exercise worksheets, procedures, laboratory setting, testing procedures, collecting and…

Working with soils: soil science continuing professional development

NASA Astrophysics Data System (ADS)

Hannam, Jacqueline; Thompson, Dick

2017-04-01

The British Society of Soil Science launched the Working with Soils professional competency programme in 2011. This was in response to concerns from practitioners and professionals of a significant skills gap in various sectors that require soil science skills. The programme includes one and two day courses that cover the qualifications, knowledge and skills required of a professional scientist or engineer conducting a range of contract work. All courses qualify for continuing professional development points with various professional practice schemes. Three courses cover the foundations of soil science namely; describing a soil profile, soil classification and understanding soil variability in the field and landscape. Other tailored courses relate to specific skills required from consultants particularly in the planning process where land is assessed for agricultural quality (agricultural land classification). New courses this year include soil handling and restoration that provides practitioners with knowledge of the appropriate management of large volumes of soil that are disturbed during development projects. The courses have so far successfully trained over 100 delegates ranging from PhD students, environmental consultants and government policy advisors.

Vulnerable land ecosystems classification using spatial context and spectral indices

NASA Astrophysics Data System (ADS)

Ibarrola-Ulzurrun, Edurne; Gonzalo-Martín, Consuelo; Marcello, Javier

2017-10-01

Natural habitats are exposed to growing pressure due to intensification of land use and tourism development. Thus, obtaining information on the vegetation is necessary for conservation and management projects. In this context, remote sensing is an important tool for monitoring and managing habitats, being classification a crucial stage. The majority of image classifications techniques are based upon the pixel-based approach. An alternative is the object-based (OBIA) approach, in which a previous segmentation step merges image pixels to create objects that are then classified. Besides, improved results may be gained by incorporating additional spatial information and specific spectral indices into the classification process. The main goal of this work was to implement and assess object-based classification techniques on very-high resolution imagery incorporating spectral indices and contextual spatial information in the classification models. The study area was Teide National Park in Canary Islands (Spain) using Worldview-2 orthoready imagery. In the classification model, two common indices were selected Normalized Difference Vegetation Index (NDVI) and Optimized Soil Adjusted Vegetation Index (OSAVI), as well as two specific Worldview-2 sensor indices, Worldview Vegetation Index and Worldview Soil Index. To include the contextual information, Grey Level Co-occurrence Matrices (GLCM) were used. The classification was performed training a Support Vector Machine with sufficient and representative number of vegetation samples (Spartocytisus supranubius, Pterocephalus lasiospermus, Descurainia bourgaeana and Pinus canariensis) as well as urban, road and bare soil classes. Confusion Matrices were computed to evaluate the results from each classification model obtaining the highest overall accuracy (90.07%) combining both Worldview indices with the GLCM-dissimilarity.

An objective and reproducible landform and topography description approach based on digital terrain analysis used for soil profile site characteristics

NASA Astrophysics Data System (ADS)

Gruber, Fabian E.; Baruck, Jasmin; Hastik, Richard; Geitner, Clemens

2015-04-01

All major soil description and classification systems, including the World Reference Base (WRB) and the German Soil description guidelines (KA5), require the characterization of landform and topography for soil profile sites. This is commonly done at more than one scale, for instance at macro-, meso- and micro scale. However, inherent when humans perform such a task, different surveyors will reach different conclusions due to their subjective perception of landscape structure, based on their individual mind-model of soil-landscape structure, emphasizing different aspects and scales of the landscape. In this study we apply a work-flow using the GRASS GIS extension module r.geomorphon to make use of high resolution digital elevation models (DEMs) to characterize the landform elements and topography of soil profile sites at different scales, and compare the results with a large number of soil profile site descriptions performed during the course of forestry surveys in South and North Tyrol (Italy and Austria, respectively). The r.geomorphon extension module for the open source geographic information system GRASS GIS applies a pattern recognition algorithm to delineate landform elements based on an input DEM. For each raster cell it computes and characterizes the visible neighborhood using line-of-sight calculations and then applies a lookup-table to classify the raster cell into one of ten landform elements (flat, peak, ridge, shoulder, slope, spur, hollow, footslope, valley and pit). The input parameter search radius (L) represents the maximum number of pixels for line-of-sight calculation, resulting in landforms larger than L to be split into landform components. The use of these visibility calculations makes this landform delineation approach suitable for comparison with the landform descriptions of soil surveyors, as their spatial perception of the landscape surrounding a soil profile site certainly influences their classification of the landform on which the profile is situated (aided by additional information such as topographic maps and aerial images). Variation of the L-value furthermore presents the opportunity to mimic the different scales at which surveyors describe soil profile locations. We first illustrate the use of r.geomorphon for site descriptions using exemplary artificial elevation profiles resembling typic catenas at different scales (L-values). We then compare the results of a landform element map computed with r.geomorphon to the relief descriptions in the test dataset. We link the surveyors' landform classification to the computed landform elements. Using a multi-scale approach we characterize raster cell locations in a way similar to the micro-, meso- and macroscale definitions used in soil survey, resulting in so-called geomorphon-signatures, such as "pit (meso-scale) located on a ridge (macro-scale)". We investigate which ranges of L-values best represent the different observation-scales as noted by soil surveyors and discuss the impacts of using a large dataset of profile location descriptions performed by different surveyors. Issues that arise are possible individual differences in landscape structure perception, but also questions regarding the accuracy of position and resulting topographic measurements in soil profile site description.

Image Analysis and Classification Based on Soil Strength

DTIC Science & Technology

2016-08-01

Satellite imagery classification is useful for a variety of commonly used ap- plications, such as land use classification, agriculture , wetland...required use of a coinci- dent digital elevation model (DEM) and a high-resolution orthophoto- graph collected by the National Agriculture Imagery Program...14. ABSTRACT Satellite imagery classification is useful for a variety of commonly used applications, such as land use classification, agriculture

Exploring the potential offered by legacy soil databases for ecosystem services mapping of Central African soils

NASA Astrophysics Data System (ADS)

Verdoodt, Ann; Baert, Geert; Van Ranst, Eric

2014-05-01

Central African soil resources are characterised by a large variability, ranging from stony, shallow or sandy soils with poor life-sustaining capabilities to highly weathered soils that recycle and support large amounts of biomass. Socio-economic drivers within this largely rural region foster inappropriate land use and management, threaten soil quality and finally culminate into a declining soil productivity and increasing food insecurity. For the development of sustainable land use strategies targeting development planning and natural hazard mitigation, decision makers often rely on legacy soil maps and soil profile databases. Recent development cooperation financed projects led to the design of soil information systems for Rwanda, D.R. Congo, and (ongoing) Burundi. A major challenge is to exploit these existing soil databases and convert them into soil inference systems through an optimal combination of digital soil mapping techniques, land evaluation tools, and biogeochemical models. This presentation aims at (1) highlighting some key characteristics of typical Central African soils, (2) assessing the positional, geographic and semantic quality of the soil information systems, and (3) revealing its potential impacts on the use of these datasets for thematic mapping of soil ecosystem services (e.g. organic carbon storage, pH buffering capacity). Soil map quality is assessed considering positional and semantic quality, as well as geographic completeness. Descriptive statistics, decision tree classification and linear regression techniques are used to mine the soil profile databases. Geo-matching as well as class-matching approaches are considered when developing thematic maps. Variability in inherent as well as dynamic soil properties within the soil taxonomic units is highlighted. It is hypothesized that within-unit variation in soil properties highly affects the use and interpretation of thematic maps for ecosystem services mapping. Results will mainly be based on analyses done in Rwanda, but can be complemented with ongoing research results or prospects for Burundi.

Remote sensing of physiographic soil units of Bennett County, South Dakota

NASA Technical Reports Server (NTRS)

Frazee, C. J.; Gropper, J. L.; Westin, F. C.

1973-01-01

A study was conducted in Bennett County, South Dakota, to establish a rangeland test site for evaluating the usefulness of ERTS data for mapping soil resources in rangeland areas. Photographic imagery obtained in October, 1970, was analyzed to determine which type of imagery is best for mapping drainage and land use patterns. Imagery of scales ranging from 1:1,000,000 to 1.20,000 was used to delineate soil-vegetative physiographic units. The photo characteristics used to define physiographic units were texture, drainage pattern, tone pattern, land use pattern and tone. These units will be used as test data for evaluating ERTS data. The physiographic units were categorized into a land classification system. The various categories which were delineated at the different scales of imagery were designed to be useful for different levels of land use planning. The land systems are adequate only for planning of large areas for general uses. The lowest category separated was the facet. The facets have a definite soil composition and represent different soil landscapes. These units are thought to be useful for providing natural resource information needed for local planning.

[Classification of enuresis/encopresis according to DSM-5].

PubMed

von Gontard, Alexander

2014-03-01

Elimination disorders are common in childhood and adolescence. Enuresis is traditionally defined as wetting from the age of 5 years and encopresis as soiling from 4 years onwards - after all organic causes have been excluded. In the past decades, many subtypes of elimination disorders have been identified with different symptoms, etiologies, and specific treatment options. Unfortunately, the DSM-5 criteria did not integrate these new approaches. In contrast, classification systems of the International Children's Incontinence Society (ICCS) for enuresis and urinary incontinence as well as the ROME-III criteria for fecal incontinence offer new and relevant suggestions for both clinical and research purposes.

A study of the utilization of ERTS-1 data from the Wabash River Basin. [crop identification, water resources, urban land use, soil mapping, and atmospheric modeling

NASA Technical Reports Server (NTRS)

Landgrebe, D. A. (Principal Investigator)

1974-01-01

The author has identified the following significant results. The most significant results were obtained in the water resources research, urban land use mapping, and soil association mapping projects. ERTS-1 data was used to classify water bodies to determine acreages and high agreement was obtained with USGS figures. Quantitative evaluation was achieved of urban land use classifications from ERTS-1 data and an overall test accuracy of 90.3% was observed. ERTS-1 data classifications of soil test sites were compared with soil association maps scaled to match the computer produced map and good agreement was observed. In some cases the ERTS-1 results proved to be more accurate than the soil association map.

Soil functional types: surveying the biophysical dimensions of soil security

NASA Astrophysics Data System (ADS)

Cécillon, Lauric; Barré, Pierre

2015-04-01

Soil is a natural capital that can deliver key ecosystem services (ES) to humans through the realization of a series of soil processes controlling ecosystem functioning. Soil is also a diverse and endangered natural resource. A huge pedodiversity has been described at all scales, which is strongly altered by global change. The multidimensional concept soil security, encompassing biophysical, economic, social, policy and legal frameworks of soils has recently been proposed, recognizing the role of soils in global environmental sustainability challenges. The biophysical dimensions of soil security focus on the functionality of a given soil that can be viewed as the combination of its capability and its condition [1]. Indeed, all soils are not equal in term of functionality. They show different processes, provide different ES to humans and respond specifically to global change. Knowledge of soil functionality in space and time is thus a crucial step towards the achievement soil security. All soil classification systems incorporate some functional information, but soil taxonomy alone cannot fully describe the functioning, limitations, resistance and resilience of soils. Droogers and Bouma [2] introduced functional variants (phenoforms) for each soil type (genoform) so as to fit more closely to soil functionality. However, different genoforms can have the same functionality. As stated by McBratney and colleagues [1], there is a great need of an agreed methodology for defining the reference state of soil functionality. Here, we propose soil functional types (SFT) as a relevant classification system for the biophysical dimensions of soil security. Following the definition of plant functional types widely used in ecology, we define a soil functional type as "a set of soil taxons or phenoforms sharing similar processes (e.g. soil respiration), similar effects on ecosystem functioning (e.g. primary productivity) and similar responses to global change (land-use, management or climate) for a particular soil-provided ecosystem service (e.g. climate regulation)". One SFT can thus include several soil types having the same functionality for a particular soil-provided ES. Another consequence is that SFT maps for two different ES may not superimpose over the same area, since some soils may fall in the same SFT for a service and in different SFT for another one. Soil functional types could be assessed and monitored in space and time by a combination of soil functional traits that correspond to inherent and manageable properties of soils. Their metrology would involve either classic (pedological observations) or advanced (molecular ecology, spectrometry, geophysics) tools. SFT could be studied and mapped at all scales, depending on the purpose of the soil security assessment (e.g. global climate modeling, land planning and management, biodiversity conservation). Overall, research is needed to find a pathway from soil pedological maps to SFT maps which would yield important benefits towards the assessment and monitoring of soil security. Indeed, this methodology would allow (i) reducing the spatial uncertainty on the assessment of ES; (ii) identifying and mapping multifunctional soils, which may be the most important soil resource to preserve. References [1] McBratney et al., 2014. Geoderma 213:203-213. [2] Droogers P, Bouma J, 1997. SSSAJ 61:1704-1710.

Testing Multivariate Adaptive Regression Splines (MARS) as a Method of Land Cover Classification of TERRA-ASTER Satellite Images.

PubMed

Quirós, Elia; Felicísimo, Angel M; Cuartero, Aurora

2009-01-01

This work proposes a new method to classify multi-spectral satellite images based on multivariate adaptive regression splines (MARS) and compares this classification system with the more common parallelepiped and maximum likelihood (ML) methods. We apply the classification methods to the land cover classification of a test zone located in southwestern Spain. The basis of the MARS method and its associated procedures are explained in detail, and the area under the ROC curve (AUC) is compared for the three methods. The results show that the MARS method provides better results than the parallelepiped method in all cases, and it provides better results than the maximum likelihood method in 13 cases out of 17. These results demonstrate that the MARS method can be used in isolation or in combination with other methods to improve the accuracy of soil cover classification. The improvement is statistically significant according to the Wilcoxon signed rank test.

Application of GIS-based Procedure on Slopeland Use Classification and Identification

NASA Astrophysics Data System (ADS)

KU, L. C.; LI, M. C.

2016-12-01

In Taiwan, the "Slopeland Conservation and Utilization Act" regulates the management of the slopelands. It categorizes the slopeland into land suitable for agricultural or animal husbandry, land suitable for forestry and land for enhanced conservation, according to the environmental factors of average slope, effective soil depth, soil erosion and parental rock. Traditionally, investigations of environmental factors require cost-effective field works. It has been confronted with many practical issues such as non-evaluated cadastral parcels, evaluation results depending on expert's opinion, difficulties in field measurement and judgment, and time consuming. This study aimed to develop a GIS-based procedure involved in the acceleration of slopeland use classification and quality improvement. First, the environmental factors of slopelands were analyzed by GIS and SPSS software. The analysis involved with the digital elevation model (DEM), soil depth map, land use map and satellite images. Second, 5% of the analyzed slopelands were selected to perform the site investigations and correct the results of classification. Finally, a 2nd examination was involved by randomly selected 2% of the analyzed slopelands to perform the accuracy evaluation. It was showed the developed procedure is effective in slopeland use classification and identification. Keywords: Slopeland Use Classification, GIS, Management

Soil gas radon concentrations measurements in terms of great soil groups.

PubMed

Içhedef, Mutlu; Saç, Müslim Murat; Camgöz, Berkay; Bolca, Mustafa; Harmanşah, Çoşkun

2013-12-01

In this study, soil gas radon concentrations were investigated according to locations, horizontal soil layers and great soil groups around Tuzla Fault, Seferihisar-İzmir. Great soil groups are a category that described the horizontal soil layers under soil classification system and distributions of radon concentration in the great soil groups are firstly determined by the present study. According to the obtained results, it has been showed that the radon concentrations in the Koluvial soil group are higher than the other soil groups in the region. Also significant differences on location in same great soil group were determined. The radon concentrations in the Koluvial soil groups were measured with respect to soil layers structures (A, B, C1, and C2). It has been observed that the values increase with depth of soil (C2>C1>B>A). The main reason may be due to the meteorological factors that have limited effect on radon escape from deep layers. Although fault lines pass thought the study area radon concentrations were varied location to location, layer to layer and great group to great group. The study shows that a detailed location description should be performed before soil radon measurements for earthquake predictions. Copyright © 2013 Elsevier Ltd. All rights reserved.

A dialog with a puzzled profile: Poetry of an old pedological discussion

NASA Astrophysics Data System (ADS)

Itkin, Danny

2017-04-01

Defining and classifying are fundamental needs in the everyday life of humans. Among quite a few relevant examples in pedology, stands the question of whether soils and some types of sediments should or can be distinct. This issue is as old as soil science itself and is possibly very much related to the never ending debate regarding "the definition of soil". As is the case in many fields, the necessity of humans to create and keep a uniform common language might collide with different cultural and/or scientific perspectives. Such is the case with the wide variety of soil classifications found throughout the world. One can easily note this diversity when reading publications that address two similar regolith profiles from different locations round the globe. In some cases it would be impossible to correlate two comparable profiles when using different classification systems. This contradictory situation is one of the most challenging topics in pedology. This whole background gave the inspiration for the following poem, titled "A dialog with a puzzled profile": Are you a soil or a sediment? Ask the oak, see if he knows. Ask him whether these are peds Or maybe a bedrock under his toes. And if you're a soil, what are you? It depends on the viewpoint, you see: Some define me with Soil Taxonomy, While others with WRB. For Hutton and Lyell I'm a weathered rock, Yet Hilgard and Dokuchaev dispute. If you ask me, well I'm a 'pedosediment', I couldn't care less for the suit. If it helps you I'll be whatever it takes,
Making sure that no one will lose. I know it depends very much on the platform Where experts are setting the rules.

The 'Soil Cover App' - a new tool for fast determination of dead and living biomass on soil

NASA Astrophysics Data System (ADS)

Bauer, Thomas; Strauss, Peter; Riegler-Nurscher, Peter; Prankl, Johann; Prankl, Heinrich

2017-04-01

Worldwide many agricultural practices aim on soil protection strategies using living or dead biomass as soil cover. Especially for the case when management practices are focusing on soil erosion mitigation the effectiveness of these practices is directly driven by the amount of soil coverleft on the soil surface. Hence there is a need for quick and reliable methods of soil cover estimation not only for living biomass but particularly for dead biomass (mulch). Available methods for the soil cover measurement are either subjective, depending on an educated guess or time consuming, e.g., if the image is analysed manually at grid points. We therefore developed a mobile application using an algorithm based on entangled forest classification. The final output of the algorithm gives classified labels for each pixel of the input image as well as the percentage of each class which are living biomass, dead biomass, stones and soil. Our training dataset consisted of more than 250 different images and their annotated class information. Images have been taken in a set of different environmental conditions such as light, soil coverages from between 0% to 100%, different materials such as living plants, residues, straw material and stones. We compared the results provided by our mobile application with a data set of 180 images that had been manually annotated A comparison between both methods revealed a regression slope of 0.964 with a coefficient of determination R2 = 0.92, corresponding to an average error of about 4%. While average error of living plant classification was about 3%, dead residue classification resulted in an 8% error. Thus the new mobile application tool offers a fast and easy way to obtain information on the protective potential of a particular agricultural management site.

Coastal plain soils and geomorphology: a key to understanding forest hydrology

Treesearch

Thomas M. Williams; Devendra M. Amatya

2016-01-01

In the 1950s, Coile published a simple classification of southeastern coastal soils using three characteristics: drainage class, sub-soil depth, and sub-soil texture. These ideas were used by Warren Stuck and Bill Smith to produce a matrix of soils with drainage class as one ordinate and subsoil texture as the second for the South Carolina coastal plain. Soils...

Soil mechanics on the Moon, Mars, and Mulberry

NASA Technical Reports Server (NTRS)

Carrier, W. D., III

1988-01-01

From a soil mechanics point of view, the Moon is a relatively simple place. Without any water, organics, or clay minerals, the geotechnical properties of the lunar soil are confined to a fairly limited range. Furthermore, the major soil-forming agent is meteorite impact, which breaks the big particles into little particles; and simultaneously, cements the little particles back together again with molten glass. After about a hundred million years of exposure to meteorite impact, the distribution of particle sizes in the soil achieves a sort of steady state. The majority of the returned lunar soil samples have been found to be well-graded silty-sand to sandy-silt (SM in the Unified Soil Classification System). Each of the particle size distributions plots within a relatively narrow band, which appears to be uniform over the entire lunar surface. This further restricts the range of physical properties of the lunar surface. In contrast, Martian soils should exhibit an extremely wide range of properties. We already know that there is a small amount of water in the soil, greater than in the Martian atmosphere. Furthermore, the soil is suspected to be smectitic clay. That makes two out of the three factors that greatly affect the properties of terrestrial soils.

Ecological classification systems for the Wayne National Forest, southeastern Ohio

Treesearch

David M. Hix; Jeffrey N. Pearcy

1997-01-01

The importance of basing land management decisions upon an ecosystem perspective is becoming widely accepted. It is frequently regarded as insufficient to simply manage stands or forest cover types without considering the ecological relationships of the forest vegetation to the other components of the ecosystems, such as soils and physiography. In order to implement...

A preliminary test of estimating forest site quality using species composition in a southern Appalachian watershed

Treesearch

W. Henry McNab; David L. Loftis

2013-01-01

Characteristic arborescent communities of mesophytic or xerophytic species have long been recognized as indicative of forest site quality in the Southern Appalachians, where soil moisture availability is the primary environmental variable affecting productivity. But, a workable quantitative system of site classification based on species composition is not available. We...

Land use surveys by means of automatic interpretation of LANDSAT system data

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Lombardo, M. A.; Novo, E. M. L. D.; Niero, M.; Foresti, C.

1981-01-01

Analyses for seven land-use classes are presented. The classes are: urban area, industrial area, bare soil, cultivated area, pastureland, reforestation, and natural vegetation. The automatic classification of LANDSAT MSS data using a maximum likelihood algorithm shows a 39% average error of emission and a 3.45 error of commission for the seven classes.

The comparative evaluation of ERTS-1 imagery for resource inventory in land use planning. [Oregon

NASA Technical Reports Server (NTRS)

Simonson, G. H. (Principal Investigator); Paine, D. P.; Lawrence, R. D.; Pyott, W. T.; Herzog, J. H.; Murray, R. J.; Norgren, J. A.; Cornwell, J. A.; Rogers, R. A.

1973-01-01

The author has identified the following significant results. Multidiscipline team interpretation and mapping of resources for Crook County is nearly complete on 1:250,000 scale enlargements of ERTS-1 imagery. Maps of geology, landforms, soils and vegetation-land use are being interpreted to show limitations, suitabilities and geologic hazards for land use planning. Mapping of lineaments and structures from ERTS-1 imagery has shown a number of features not previously mapped in Oregon. A timber inventory of Ochoco National Forest has been made. Inventory of forest clear-cutting practices has been successfully demonstrated with ERTS-1 color composites. Soil tonal differences in fallow fields shown on ERTS-1 correspond with major soil boundaries in loess-mantled terrain. A digital classification system used for discriminating natural vegetation and geologic materials classes has been successful in separation of most major classes around Newberry Cauldera, Mt. Washington and Big Summit Prairie. Computer routines are available for correction of scanner data variations; and for matching scales and coordinates between digital and photographic imagery. Methods of Diazo film color printing of computer classifications and elevation-slope perspective plots with computer are being developed.

Intrinsic Remediation Engineering Evaluation/Cost Analysis for Car Care Center at Bolling Air Force Base, Washington, DC

DTIC Science & Technology

1997-01-01

supplemented using established literature values for similar aquifer materials . The groundwater sampling activities and analytical results from both...subsurface materials recovered. Observed soil classification types compared very favorably to the soil classifications determined by the CPT tests. 0 2.1.5...other similar substances were handled in a manner consistent with accepted safety procedures and standard operating practices. Well completion materials

Impacts of soil moisture content on visual soil evaluation

NASA Astrophysics Data System (ADS)

Emmet-Booth, Jeremy; Forristal, Dermot; Fenton, Owen; Bondi, Giulia; Creamer, Rachel; Holden, Nick

2017-04-01

Visual Soil Examination and Evaluation (VSE) techniques offer tools for soil quality assessment. They involve the visual and tactile assessment of soil properties such as aggregate size and shape, porosity, redox morphology, soil colour and smell. An increasing body of research has demonstrated the reliability and utility of VSE techniques. However a number of limitations have been identified, including the potential impact of soil moisture variation during sampling. As part of a national survey of grassland soil quality in Ireland, an evaluation of the impact of soil moisture on two widely used VSE techniques was conducted. The techniques were Visual Evaluation of Soil Structure (VESS) (Guimarães et al., 2011) and Visual Soil Assessment (VSA) (Shepherd, 2009). Both generate summarising numeric scores that indicate soil structural quality, though employ different scoring mechanisms. The former requires the assessment of properties concurrently and the latter separately. Both methods were deployed on 20 sites across Ireland representing a range of soils. Additional samples were taken for soil volumetric water (θ) determination at 5-10 and 10-20 cm depth. No significant correlation was observed between θ 5-10 cm and either VSE technique. However, VESS scores were significantly related to θ 10-20 cm (rs = 0.40, sig = 0.02) while VSA scores were not (rs = -0.33, sig = 0.06). VESS and VSA scores can be grouped into quality classifications (good, moderate and poor). No significant mean difference was observed between θ 5-10 cm or θ 10-20 cm according to quality classification by either method. It was concluded that VESS scores may be affected by soil moisture variation while VSA appear unaffected. The different scoring mechanisms, where the separate assessment and scoring of individual properties employed by VSA, may limit soil moisture effects. However, moisture content appears not to affect overall structural quality classification by either method. References Guimarães, R.M.C., Ball, B.C. & Tormena, C.A. 2011. Improvements in the visual evaluation of soil structure, Soil Use and Management, 27, 3: 395-403 Shepherd, G.T. 2009. Visual Soil Assessment. Field guide for pastoral grazing and cropping on flat to rolling country. 2nd edn. Horizons regional council, New Zealand.

U.S. Fish and Wildlife Service 1979 wetland classification: a review

USGS Publications Warehouse

Cowardin, L.M.; Golet, F.C.

1995-01-01

In 1979 the US Fish and Wildlife Service published and adopted a classification of wetlands and deepwater habitats of the United States. The system was designed for use in a national inventory of wetlands. It was intended to be ecologically based, to furnish the mapping units needed for the inventory, and to provide national consistency in terminology and definition. We review the performance of the classification after 13 years of use. The definition of wetland is based on national lists of hydric soils and plants that occur in wetlands. Our experience suggests that wetland classifications must facilitate mapping and inventory because these data gathering functions are essential to management and preservation of the wetland resource, but the definitions and taxa must have ecological basis. The most serious problem faced in construction of the classification was lack of data for many of the diverse wetland types. Review of the performance of the classification suggests that, for the most part, it was successful in accomplishing its objectives, but that problem areas should be corrected and modification could strengthen its utility. The classification, at least in concept, could be applied outside the United States. Experience gained in use of the classification can furnish guidance as to pitfalls to be avoided in the wetland classification process.

Classification and spatial mapping of riparian habitat with applications toward management of streams impacted by nonpoint source pollution

NASA Astrophysics Data System (ADS)

Delong, Michael D.; Brusven, Merlyn A.

1991-07-01

Management of riparian habitats has been recognized for its importance in reducing instream effects of agricultural nonpoint source pollution. By serving as a buffer, well structured riparian habitats can reduce nonpoint source impacts by filtering surface runoff from field to stream. A system has been developed where key characteristics of riparian habitat, vegetation type, height, width, riparian and shoreline bank slope, and land use are classified as discrete categorical units. This classification system recognizes seven riparian vegetation types, which are determined by dominant plant type. Riparian and shoreline bank slope, in addition to riparian width and height, each consist of five categories. Classification by discrete units allows for ready digitizing of information for production of spatial maps using a geographic information system (GIS). The classification system was tested for field efficiency on Tom Beall Creek watershed, an agriculturally impacted third-order stream in the Clearwater River drainage, Nez Perce County, Idaho, USA. The classification system was simple to use during field applications and provided a good inventory of riparian habitat. After successful field tests, spatial maps were produced for each component using the Professional Map Analysis Package (pMAP), a GIS program. With pMAP, a map describing general riparian habitat condition was produced by combining the maps of components of riparian habitat, and the condition map was integrated with a map of soil erosion potential in order to determine areas along the stream that are susceptible to nonpoint source pollution inputs. Integration of spatial maps of riparian classification and watershed characteristics has great potential as a tool for aiding in making management decisions for mitigating off-site impacts of agricultural nonpoint source pollution.

Crop classification using multidate/multifrequency radar data. [Colby, Kansas

NASA Technical Reports Server (NTRS)

Ulaby, F. T. (Principal Investigator); Shanmugam, K. S.; Narayanan, V.; Dobson, C.

1981-01-01

Both C- and L-band radar data acquired over a test site near Colby, Kansas during the summer of 1978 were used to identify three types of vegetation cover and bare soil. The effects of frequency, polarization, and the look angle on the overall accuracy of recognizing the four types of ground cover were analyzed. In addition, multidate data were used to study the improvement in recognition accuracy possible with the addition of temporal information. The soil moisture conditions had changed considerably during the temporal sequence of the data; hence, the effects of soil moisture on the ability to discriminate between cover types were also analyzed. The results provide useful information needed for selecting the parameters of a radar system for monitoring crops.

Global hierarchical classification of deepwater and wetland environments from remote sensing products

NASA Astrophysics Data System (ADS)

Fluet-Chouinard, E.; Lehner, B.; Aires, F.; Prigent, C.; McIntyre, P. B.

2017-12-01

Global surface water maps have improved in spatial and temporal resolutions through various remote sensing methods: open water extents with compiled Landsat archives and inundation with topographically downscaled multi-sensor retrievals. These time-series capture variations through time of open water and inundation without discriminating between hydrographic features (e.g. lakes, reservoirs, river channels and wetland types) as other databases have done as static representation. Available data sources present the opportunity to generate a comprehensive map and typology of aquatic environments (deepwater and wetlands) that improves on earlier digitized inventories and maps. The challenge of classifying surface waters globally is to distinguishing wetland types with meaningful characteristics or proxies (hydrology, water chemistry, soils, vegetation) while accommodating limitations of remote sensing data. We present a new wetland classification scheme designed for global application and produce a map of aquatic ecosystem types globally using state-of-the-art remote sensing products. Our classification scheme combines open water extent and expands it with downscaled multi-sensor inundation data to capture the maximal vegetated wetland extent. The hierarchical structure of the classification is modified from the Cowardin Systems (1979) developed for the USA. The first level classification is based on a combination of landscape positions and water source (e.g. lacustrine, riverine, palustrine, coastal and artificial) while the second level represents the hydrologic regime (e.g. perennial, seasonal, intermittent and waterlogged). Class-specific descriptors can further detail the wetland types with soils and vegetation cover. Our globally consistent nomenclature and top-down mapping allows for direct comparison across biogeographic regions, to upscale biogeochemical fluxes as well as other landscape level functions.

Digital soil classification and elemental mapping using imaging Vis-NIR spectroscopy: How to explicitly quantify stagnic properties of a Luvisol under Norway spruce

NASA Astrophysics Data System (ADS)

Kriegs, Stefanie; Buddenbaum, Henning; Rogge, Derek; Steffens, Markus

2015-04-01

Laboratory imaging Vis-NIR spectroscopy of soil profiles is a novel technique in soil science that can determine quantity and quality of various chemical soil properties with a hitherto unreached spatial resolution in undisturbed soil profiles. We have applied this technique to soil cores in order to get quantitative proof of redoximorphic processes under two different tree species and to proof tree-soil interactions at microscale. Due to the imaging capabilities of Vis-NIR spectroscopy a spatially explicit understanding of soil processes and properties can be achieved. Spatial heterogeneity of the soil profile can be taken into account. We took six 30 cm long rectangular soil columns of adjacent Luvisols derived from quaternary aeolian sediments (Loess) in a forest soil near Freising/Bavaria using stainless steel boxes (100×100×300 mm). Three profiles were sampled under Norway spruce and three under European beech. A hyperspectral camera (VNIR, 400-1000 nm in 160 spectral bands) with spatial resolution of 63×63 µm² per pixel was used for data acquisition. Reference samples were taken at representative spots and analysed for organic carbon (OC) quantity and quality with a CN elemental analyser and for iron oxides (Fe) content using dithionite extraction followed by ICP-OES measurement. We compared two supervised classification algorithms, Spectral Angle Mapper and Maximum Likelihood, using different sets of training areas and spectral libraries. As established in chemometrics we used multivariate analysis such as partial least-squares regression (PLSR) in addition to multivariate adaptive regression splines (MARS) to correlate chemical data with Vis-NIR spectra. As a result elemental mapping of Fe and OC within the soil core at high spatial resolution has been achieved. The regression model was validated by a new set of reference samples for chemical analysis. Digital soil classification easily visualizes soil properties within the soil profiles. By combining both techniques, detailed soil maps, elemental balances and a deeper understanding of soil forming processes at the microscale become feasible for complete soil profiles.

Combining Soil Databases for Topsoil Organic Carbon Mapping in Europe.

PubMed

Aksoy, Ece; Yigini, Yusuf; Montanarella, Luca

2016-01-01

Accuracy in assessing the distribution of soil organic carbon (SOC) is an important issue because of playing key roles in the functions of both natural ecosystems and agricultural systems. There are several studies in the literature with the aim of finding the best method to assess and map the distribution of SOC content for Europe. Therefore this study aims searching for another aspect of this issue by looking to the performances of using aggregated soil samples coming from different studies and land-uses. The total number of the soil samples in this study was 23,835 and they're collected from the "Land Use/Cover Area frame Statistical Survey" (LUCAS) Project (samples from agricultural soil), BioSoil Project (samples from forest soil), and "Soil Transformations in European Catchments" (SoilTrEC) Project (samples from local soil data coming from six different critical zone observatories (CZOs) in Europe). Moreover, 15 spatial indicators (slope, aspect, elevation, compound topographic index (CTI), CORINE land-cover classification, parent material, texture, world reference base (WRB) soil classification, geological formations, annual average temperature, min-max temperature, total precipitation and average precipitation (for years 1960-1990 and 2000-2010)) were used as auxiliary variables in this prediction. One of the most popular geostatistical techniques, Regression-Kriging (RK), was applied to build the model and assess the distribution of SOC. This study showed that, even though RK method was appropriate for successful SOC mapping, using combined databases was not helpful to increase the statistical significance of the method results for assessing the SOC distribution. According to our results; SOC variation was mainly affected by elevation, slope, CTI, average temperature, average and total precipitation, texture, WRB and CORINE variables for Europe scale in our model. Moreover, the highest average SOC contents were found in the wetland areas; agricultural areas have much lower soil organic carbon content than forest and semi natural areas; Ireland, Sweden and Finland has the highest SOC, on the contrary, Portugal, Poland, Hungary, Spain, Italy have the lowest values with the average 3%.

Combining Soil Databases for Topsoil Organic Carbon Mapping in Europe

PubMed Central

Aksoy, Ece

2016-01-01

Accuracy in assessing the distribution of soil organic carbon (SOC) is an important issue because of playing key roles in the functions of both natural ecosystems and agricultural systems. There are several studies in the literature with the aim of finding the best method to assess and map the distribution of SOC content for Europe. Therefore this study aims searching for another aspect of this issue by looking to the performances of using aggregated soil samples coming from different studies and land-uses. The total number of the soil samples in this study was 23,835 and they’re collected from the “Land Use/Cover Area frame Statistical Survey” (LUCAS) Project (samples from agricultural soil), BioSoil Project (samples from forest soil), and “Soil Transformations in European Catchments” (SoilTrEC) Project (samples from local soil data coming from six different critical zone observatories (CZOs) in Europe). Moreover, 15 spatial indicators (slope, aspect, elevation, compound topographic index (CTI), CORINE land-cover classification, parent material, texture, world reference base (WRB) soil classification, geological formations, annual average temperature, min-max temperature, total precipitation and average precipitation (for years 1960–1990 and 2000–2010)) were used as auxiliary variables in this prediction. One of the most popular geostatistical techniques, Regression-Kriging (RK), was applied to build the model and assess the distribution of SOC. This study showed that, even though RK method was appropriate for successful SOC mapping, using combined databases was not helpful to increase the statistical significance of the method results for assessing the SOC distribution. According to our results; SOC variation was mainly affected by elevation, slope, CTI, average temperature, average and total precipitation, texture, WRB and CORINE variables for Europe scale in our model. Moreover, the highest average SOC contents were found in the wetland areas; agricultural areas have much lower soil organic carbon content than forest and semi natural areas; Ireland, Sweden and Finland has the highest SOC, on the contrary, Portugal, Poland, Hungary, Spain, Italy have the lowest values with the average 3%. PMID:27011357

Agro-hydrologic landscapes in the Upper Mississippi and Ohio River basins.

PubMed

Schilling, Keith E; Wolter, Calvin F; McLellan, Eileen

2015-03-01

A critical part of increasing conservation effectiveness is targeting the "right practice" to the "right place" where it can intercept pollutant flowpaths. Conceptually, these flowpaths can be inferred from soil and slope characteristics, and in this study, we developed an agro-hydrologic classification to identify N and P loss pathways and priority conservation practices in small watersheds in the U.S. Midwest. We developed a GIS framework to classify 11,010 small watersheds in the Upper Mississippi and Ohio River basins based on soil permeability and slope characteristics of agricultural cropland areas in each watershed. The amount of cropland in any given watershed varied from <10 to >60 %. Cropland areas were classified into five main categories, with slope classes of <2, 2-5, and >5 %, and soil drainage classes of poorly and well drained. Watersheds in the Upper Mississippi River basin (UMRB) were dominated by cropland areas in low slopes and poorly drained soils, whereas less-intensively cropped watersheds in Wisconsin and Minnesota (in the UMRB) and throughout the Ohio River basin were overwhelmingly well drained. Hydrologic differences in cropped systems indicate that a one-size-fits-all approach to conservation selection will not work. Consulting the classification scheme proposed herein may be an appropriate first-step in identifying those conservation practices that might be most appropriate for small watersheds in the basin.

Advanced Land Use Classification for Nigeriasat-1 Image of Lake Chad Basin

NASA Astrophysics Data System (ADS)

Babamaaji, R.; Park, C.; Lee, J.

2009-12-01

Lake Chad is a shrinking freshwater lake that has been significantly reduced to about 1/20 of its original size in the 1960’s. The severe draughts in 1970’s and 1980’s and following overexploitations of water resulted in the shortage of surface water in the lake and the surrounding rivers. Ground water resources are in scarcity too as ground water recharge is mostly made by soil infiltration through soil and land cover, but this surface cover is now experiencing siltation and expansion of wetland with invasive species. Large changes in land use and water management practices have taken place in the last 50 years including: removal of water from river systems for irrigation and consumption, degradation of forage land by overgrazing, deforestation, replacing natural ecosystems with mono-cultures, and construction of dams. Therefore, understanding the change of land use and its characteristics must be a first step to find how such changes disturb the water cycle around the lake and affect the shrinkage of the lake. Before any useful thematic information can be extracted from remote sensing data, a land cover classification system has to be developed to obtain the classes of interest. A combination of classification systems used by Global land cover, Water Resources eAtlass and Lake Chad Basin Commission gave rise to 7 land cover classes comprising of - Cropland, vegetation, grassland, water body, shrub-land, farmland ( mostly irrigated) and bareland (i.e. clear land). Supervised Maximum likelihood classification method was used with 15 reference points per class chosen. At the end of the classification, the overall accuracy is 93.33%. Producer’s accuracy for vegetation is 40% compare to the user’s accuracy that is 66.67 %. The reason is that the vegetation is similar to shrub land, it is very hard to differentiate between the vegetation and other plants, and therefore, most of the vegetation is classified as shrub land. Most of the waterbodies are occupied by vegetation and other plant, therefore it can only be well identify if producer is present or using high resolution image, which is shown in the accuracy result of water for both producer and user (66.67%).

Development of a channel classification to evaluate potential for cottonwood restoration, lower segments of the Middle Missouri River, South Dakota and Nebraska

USGS Publications Warehouse

Jacobson, Robert B.; Elliott, Caroline M.; Huhmann, Brittany L.

2010-01-01

This report documents development of a spatially explicit river and flood-plain classification to evaluate potential for cottonwood restoration along the Sharpe and Fort Randall segments of the Middle Missouri River. This project involved evaluating existing topographic, water-surface elevation, and soils data to determine if they were sufficient to create a classification similar to the Land Capability Potential Index (LCPI) developed by Jacobson and others (U.S. Geological Survey Scientific Investigations Report 2007–5256) and developing a geomorphically based classification to apply to evaluating restoration potential.Existing topographic, water-surface elevation, and soils data for the Middle Missouri River were not sufficient to replicate the LCPI. The 1/3-arc-second National Elevation Dataset delineated most of the topographic complexity and produced cumulative frequency distributions similar to a high-resolution 5-meter topographic dataset developed for the Lower Missouri River. However, lack of bathymetry in the National Elevation Dataset produces a potentially critical bias in evaluation of frequently flooded surfaces close to the river. High-resolution soils data alone were insufficient to replace the information content of the LCPI. In test reaches in the Lower Missouri River, soil drainage classes from the Soil Survey Geographic Database database correctly classified 0.8–98.9 percent of the flood-plain area at or below the 5-year return interval flood stage depending on state of channel incision; on average for river miles 423–811, soil drainage class correctly classified only 30.2 percent of the flood-plain area at or below the 5-year return interval flood stage. Lack of congruence between soil characteristics and present-day hydrology results from relatively rapid incision and aggradation of segments of the Missouri River resulting from impoundments and engineering. The most sparsely available data in the Middle Missouri River were water-surface elevations. Whereas hydraulically modeled water-surface elevations were available at 1.6-kilometer intervals in the Lower Missouri River, water-surface elevations in the Middle Missouri River had to be interpolated between streamflow-gaging stations spaced 3–116 kilometers. Lack of high-resolution water-surface elevation data precludes development of LCPI-like classification maps.An hierarchical river classification framework is proposed to provide structure for a multiscale river classification. The segment-scale classification presented in this report is deductive and based on presumed effects of dams, significant tributaries, and geological (and engineered) channel constraints. An inductive reach-scale classification, nested within the segment scale, is based on multivariate statistical clustering of geomorphic data collected at 500-meter intervals along the river. Cluster-based classifications delineate reaches of the river with similar channel and flood-plain geomorphology, and presumably, similar geomorphic and hydrologic processes. The dominant variables in the clustering process were channel width (Fort Randall) and valley width (Sharpe), followed by braiding index (both segments).Clusters with multithread and highly sinuous channels are likely to be associated with dynamic channel migration and deposition of fresh, bare sediment conducive to natural cottonwood germination. However, restoration potential within these reaches is likely to be mitigated by interaction of cottonwood life stages with the highly altered flow regime.

Virtual Soil Monoliths: Blending Traditional and Web-Based Educational Approaches

ERIC Educational Resources Information Center

Krzic, Maja; Strivelli, Rachel A.; Holmes, Emma; Grand, Stephanie; Dyanatkar, Saeed; Lavkulich, Les M.; Crowley, Chris

2013-01-01

Since soil plays a crucial role in all aspects of global environmental change, it is essential that post-secondary institutions provide students with a strong foundation in soil science concepts including soil classification. The onset of information technology (IT) and web-based multimedia have opened new avenues to better incorporate…

Pedodiversity and Its Significance in the Context of Modern Soil Geography

NASA Astrophysics Data System (ADS)

Krasilnikov, P. V.; Gerasimova, M. I.; Golovanov, D. L.; Konyushkova, M. V.; Sidorova, V. A.; Sorokin, A. S.

2018-01-01

Methodological basics of the study and quantitative assessment of pedodiversity are discussed. It is shown that the application of various indices and models of pedodiversity can be feasible for solving three major issues in pedology: a comparative geographical analysis of different territories, a comparative historical analysis of soil development in the course of landscape evolution, and the analysis of relationships between biodiversity and pedodiversity. Analogous geographic concepts of geodiversity and landscape diversity are also discussed. Certain limitations in the use of quantitative estimates of pedodiversity related to their linkage to the particular soil classification systems and with the initial soil maps are considered. Problems of the interpretation of the results of pedodiversity assessments are emphasized. It is shown that scientific explanations of biodiversity cannot be adequately applied in soil studies. Promising directions of further studies of pedodiversity are outlined. They include the assessment of the functional diversity of soils on the basis of data on their properties, integration with geostatistical methods of evaluation of soil variability, and assessment of pedodiversity on different scales.

Trophic position of soil nematodes in boreal forests as indicated by stable isotope analysis

NASA Astrophysics Data System (ADS)

Kudrin, Alexey; Tsurikov, Sergey

2016-04-01

Despite the well-developed trophic classification of soil nematodes, their position in soil food webs is still little understood. Observed deviations from the typical feeding strategy indicate that a simplified trophic classification probably does not fully reflect actual trophic interactions. Furthermore, the extent and functional significance of nematodes as prey for other soil animals remains unknown. Stable isotope analysis (SIA) is powerful tool for investigating the structure of soil food webs, but its application to the study of soil nematodes has been limited to only a few studies. We used stable isotope analysis to gain a better understanding of trophic links of several groups of soil nematodes in two boreal forests on albeluvisol. We investigated four taxonomic groups of nematodes: Mononchida, Dorylaimida, Plectidae and Tylenchidae (mostly from the genus Filenchus), that according to the conventional trophic classification represent predators, omnivores, bacterivores and root-fungal feeders, respectively. To assess the trophic position of nematodes, we used a comparison against a set of reference species including herbivorous, saprophagous and predatory macro-invertebrates, oribatid and mesostigmatid mites, and collembolans. Our results suggest that trophic position of the investigated groups of soil nematodes generally corresponds to the conventional classification. All nematodes were enriched in 13C relative to Picea abies roots and litter, and mycorrhizal fungal mycelium. Root-fungal feeders Tylenchidae had δ15N values similar to those of earthworms, enchytraeids and Entomobrya collembolans, but slightly lower δ13C values. Bacterivorous Plectidae were either equal or enriched in 15N compared with saprophagous macroinvertebrates and most mesofauna species. Omnivorous Dorylaimida and predatory Mononchida were further enriched in 15N and their isotopic signature was similar to that of predatory arthropods. These data confirm a clear separation of nematodes into saprophagous/microbial feeders (Tylenchidae and Plectidae) and predators (Mononchida and Dorylaimida). Furthermore, they suggest that Mononchida and Dorylaimida use different sources of carbon, though exact trophic links remain unclear. As a rule, nematodes were either equal or higher in δ15N values relative to most microbivorous microarthropods, contradicting an emerging view that soil nematodes can be an important prey for a wide range of oribatid mites and collembolans. Patterns of the isotopic signatures suggest that soil nematodes and the bulk of soil animals depend on resources derived from a dominating upper-canopy tree (Picea abies) via the detrital, rather than mycorrhizal pathway.

Digital mapping of soil properties in Zala County, Hungary for the support of county-level spatial planning and land management

NASA Astrophysics Data System (ADS)

Pásztor, László; Laborczi, Annamária; Szatmári, Gábor; Fodor, Nándor; Bakacsi, Zsófia; Szabó, József; Illés, Gábor

2014-05-01

The main objective of the DOSoReMI.hu (Digital, Optimized, Soil Related Maps and Information in Hungary) project is to significantly extend the potential, how demands on spatial soil related information could be satisfied in Hungary. Although a great amount of soil information is available due to former mappings and surveys, there are more and more frequently emerging discrepancies between the available and the expected data. The gaps are planned to be filled with optimized DSM products heavily based on legacy soil data, which still represent a valuable treasure of soil information at the present time. Impact assessment of the forecasted climate change and the analysis of the possibilities of the adaptation in the agriculture and forestry can be supported by scenario based land management modelling, whose results can be incorporated in spatial planning. This framework requires adequate, preferably timely and spatially detailed knowledge of the soil cover. For the satisfaction of these demands in Zala County (one of the nineteen counties of Hungary), the soil conditions of the agricultural areas were digitally mapped based on the most detailed, available recent and legacy soil data. The agri-environmental conditions were characterized according to the 1:10,000 scale genetic soil mapping methodology and the category system applied in the Hungarian soil-agricultural chemistry practice. The factors constraining the fertility of soils were featured according to the biophysical criteria system elaborated for the delimitation of naturally handicapped areas in the EU. Production related soil functions were regionalized incorporating agro-meteorological modelling. The appropriate derivatives of a 20m digital elevation model were used in the analysis. Multitemporal MODIS products were selected from the period of 2009-2011 representing different parts of the growing season and years with various climatic conditions. Additionally two climatic data layers, the 1:100.000 Geological Map of Hungary and the map of groundwater depth were used as auxiliary environmental covariables. Various soil related information were mapped in three distinct sets: (i) basic soil properties determining agri-environmental conditions (soil type according to the Hungarian genetic classification, rootable depth, sand and clay content for the 1st and 2nd soil layers, pH, OM and carbonate content for the plough layer); (ii) biophysical criteria of natural handicaps defined by common European system and (iii) agro-meteorologically modelled yield values for different crops, meteorological and management scenarios. The applied method(s) for the spatial inference of specific themes was/were suitably selected: regression and classification trees for categorical data, indicator kriging for probabilistic management of criterion information; and typically regression kriging for quantitative data. Our paper will present the mapping processes themselves, the resulted maps and some conclusions drawn from the experiences. Acknowledgement: Our work was supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167) and by the European Union with the co-financing of the European Social Fund (TÁMOP-4.2.2.A-11/1/KONV-2012-0013.).

Spatial Prediction of Soil Classes by Using Soil Weathering Parameters Derived from vis-NIR Spectroscopy

NASA Astrophysics Data System (ADS)

Ramirez-Lopez, Leonardo; Alexandre Dematte, Jose

2010-05-01

There is consensus in the scientific community about the great need of spatial soil information. Conventional mapping methods are time consuming and involve high costs. Digital soil mapping has emerged as an area in which the soil mapping is optimized by the application of mathematical and statistical approaches, as well as the application of expert knowledge in pedology. In this sense, the objective of the study was to develop a methodology for the spatial prediction of soil classes by using soil spectroscopy methodologies related with fieldwork, spectral data from satellite image and terrain attributes in simultaneous. The studied area is located in São Paulo State, and comprised an area of 473 ha, which was covered by a regular grid (100 x 100 m). In each grid node was collected soil samples at two depths (layers A and B). There were extracted 206 samples from transect sections and submitted to soil analysis (clay, Al2O3, Fe2O3, SiO2 TiO2, and weathering index). The first analog soil class map (ASC-N) contains only soil information regarding from orders to subgroups of the USDA Soil Taxonomy System. The second (ASC-H) map contains some additional information related to some soil attributes like color, ferric levels and base sum. For the elaboration of the digital soil maps the data was divided into three groups: i) Predicted soil attributes of the layer B (related to the soil weathering) which were obtained by using a local soil spectral library; ii) Spectral bands data extracted from a Landsat image; and iii) Terrain parameters. This information was summarized by a principal component analysis (PCA) in each group. Digital soil maps were generated by supervised classification using a maximum likelihood method. The trainee information for this classification was extracted from five toposequences based on the analog soil class maps. The spectral models of weathering soil attributes shown a high predictive performance with low error (R2 0.71 to 0.90). The spatial prediction of these attributes also showed a high performance (validations with R2> 0.78). These models allowed to increase spatial resolution of soil weathering information. On the other hand, the comparison between the analog and digital soil maps showed a global accuracy of 69% for the ASC-N map and 62% in the ASC-H map, with kappa indices of 0.52 and 0.45 respectively.

Using greenhouse gas fluxes to define soil functional types

DOE Office of Scientific and Technical Information (OSTI.GOV)

Petrakis, Sandra; Barba, Josep; Bond-Lamberty, Ben

Soils provide key ecosystem services and directly control ecosystem functions; thus, there is a need to define the reference state of soil functionality. Most common functional classifications of ecosystems are vegetation-centered and neglect soil characteristics and processes. We propose Soil Functional Types (SFTs) as a conceptual approach to represent and describe the functionality of soils based on characteristics of their greenhouse gas (GHG) flux dynamics. We used automated measurements of CO2, CH4 and N2O in a forested area to define SFTs following a simple statistical framework. This study supports the hypothesis that SFTs provide additional insights on the spatial variabilitymore » of soil functionality beyond information represented by commonly measured soil parameters (e.g., soil moisture, soil temperature, litter biomass). We discuss the implications of this framework at the plot-scale and the potential of this approach at larger scales. This approach is a first step to provide a framework to define SFTs, but a community effort is necessary to harmonize any global classification for soil functionality. A global application of the proposed SFT framework will only be possible if there is a community-wide effort to share data and create a global database of GHG emissions from soils.« less

Pedoinformatics Approach to Soil Text Analytics

NASA Astrophysics Data System (ADS)

Furey, J.; Seiter, J.; Davis, A.

2017-12-01

The several extant schema for the classification of soils rely on differing criteria, but the major soil science taxonomies, including the United States Department of Agriculture (USDA) and the international harmonized World Reference Base for Soil Resources systems, are based principally on inferred pedogenic properties. These taxonomies largely result from compiled individual observations of soil morphologies within soil profiles, and the vast majority of this pedologic information is contained in qualitative text descriptions. We present text mining analyses of hundreds of gigabytes of parsed text and other data in the digitally available USDA soil taxonomy documentation, the Soil Survey Geographic (SSURGO) database, and the National Cooperative Soil Survey (NCSS) soil characterization database. These analyses implemented iPython calls to Gensim modules for topic modelling, with latent semantic indexing completed down to the lowest taxon level (soil series) paragraphs. Via a custom extension of the Natural Language Toolkit (NLTK), approximately one percent of the USDA soil series descriptions were used to train a classifier for the remainder of the documents, essentially by treating soil science words as comprising a novel language. While location-specific descriptors at the soil series level are amenable to geomatics methods, unsupervised clustering of the occurrence of other soil science words did not closely follow the usual hierarchy of soil taxa. We present preliminary phrasal analyses that may account for some of these effects.

Site effect classification based on microtremor data analysis using a concentration-area fractal model

NASA Astrophysics Data System (ADS)

Adib, A.; Afzal, P.; Heydarzadeh, K.

2015-01-01

The aim of this study is to classify the site effect using concentration-area (C-A) fractal model in Meybod city, central Iran, based on microtremor data analysis. Log-log plots of the frequency, amplification and vulnerability index (k-g) indicate a multifractal nature for the parameters in the area. The results obtained from the C-A fractal modelling reveal that proper soil types are located around the central city. The results derived via the fractal modelling were utilized to improve the Nogoshi and Igarashi (1970, 1971) classification results in the Meybod city. The resulting categories are: (1) hard soil and weak rock with frequency of 6.2 to 8 Hz, (2) stiff soil with frequency of about 4.9 to 6.2 Hz, (3) moderately soft soil with the frequency of 2.4 to 4.9 Hz, and (4) soft soil with the frequency lower than 2.4 Hz.

Site effect classification based on microtremor data analysis using concentration-area fractal model

NASA Astrophysics Data System (ADS)

Adib, A.; Afzal, P.; Heydarzadeh, K.

2014-07-01

The aim of this study is to classify the site effect using concentration-area (C-A) fractal model in Meybod city, Central Iran, based on microtremor data analysis. Log-log plots of the frequency, amplification and vulnerability index (k-g) indicate a multifractal nature for the parameters in the area. The results obtained from the C-A fractal modeling reveal that proper soil types are located around the central city. The results derived via the fractal modeling were utilized to improve the Nogoshi's classification results in the Meybod city. The resulted categories are: (1) hard soil and weak rock with frequency of 6.2 to 8 Hz, (2) stiff soil with frequency of about 4.9 to 6.2 Hz, (3) moderately soft soil with the frequency of 2.4 to 4.9 Hz, and (4) soft soil with the frequency lower than 2.4 Hz.

AmeriFlux CA-Qcu Quebec - Eastern Boreal, Black Spruce/Jack Pine Cutover

DOE Data Explorer

Margolis, Hank A. [Université Laval

2016-01-01

This is the AmeriFlux version of the carbon flux data for the site CA-Qcu Quebec - Eastern Boreal, Black Spruce/Jack Pine Cutover. Site Description - The ground is gently rolling with a weak slope (<5%). In mesic areas (designated as well to moderately well drained areas, according to the Canadian System of Soil Classification (Agriculture Canada Expert Committee on Soil Survey, 1983)), the soil is a ferro-humic to humic podzol covered by an organic layer having an average depth of 26 cm (Fig. 1). In humid areas, the soil is organic (imperfectly to poorly drained) with an average organic layer of 125 cm. Mesic areas accounted for approximately 75% of the total surface area of the footprint and humid areas accounted for 25%. Full-time continuous measurements eneded in 2011. Intermittent measurements are on-going as resources permit.

Analysis of land cover change and its driving forces in a desert oasis landscape of southern Xinjiang, China

NASA Astrophysics Data System (ADS)

Amuti, T.; Luo, G.

2014-07-01

The combined effects of drought, warming and the changes in land cover have caused severe land degradation for several decades in the extremely arid desert oases of Southern Xinjiang, Northwest China. This study examined land cover changes during 1990-2008 to characterize and quantify the transformations in the typical oasis of Hotan. Land cover classifications of these images were performed based on the supervised classification scheme integrated with conventional vegetation and soil indexes. Change-detection techniques in remote sensing (RS) and a geographic information system (GIS) were applied to quantify temporal and spatial dynamics of land cover changes. The overall accuracies, Kappa coefficients, and average annual increase rate or decrease rate of land cover classes were calculated to assess classification results and changing rate of land cover. The analysis revealed that major trends of the land cover changes were the notable growth of the oasis and the reduction of the desert-oasis ecotone, which led to accelerated soil salinization and plant deterioration within the oasis. These changes were mainly attributed to the intensified human activities. The results indicated that the newly created agricultural land along the margins of the Hotan oasis could result in more potential areas of land degradation. If no effective measures are taken against the deterioration of the oasis environment, soil erosion caused by land cover change may proceed. The trend of desert moving further inward and the shrinking of the ecotone may lead to potential risks to the eco-environment of the Hotan oasis over the next decades.

Soil evaluation for land use optimizing

NASA Astrophysics Data System (ADS)

Marinina, O. A.

2018-01-01

The article presents the method of soil classification proposed in the course of the study in which the list of indicators proposed by the existing recommendations is optimized. On the example of one of the river basins within the boundaries of the Belgorod region zoning of the territory was carried out. With this approach, the boundaries of the territorial zones are projected along the natural boundaries of natural objects and the productivity of soils is determined as the main criterion for zoning. To assess the territory by soil properties, the features of the soil cover of the river basin were studied and vectorization of the soil variety boundaries was carried out. In the land evaluation essential and useful for the growth of crops macro- and minor-nutrient elements necessary for the growth of crops were included. To compare the soils each of the indicators was translated into relative units. The final score of soil quality is calculated as the mean geometric value of scores from 0 to 100 points for the selected diagnostic features. Through the imposition of results of soil classification and proposed by the concept of basin nature management - land management activities, five zones were identified according to the degree of suitability for use in agriculture.

New best estimates for radionuclide solid-liquid distribution coefficients in soils. Part 2: naturally occurring radionuclides.

PubMed

Vandenhove, H; Gil-García, C; Rigol, A; Vidal, M

2009-09-01

Predicting the transfer of radionuclides in the environment for normal release, accidental, disposal or remediation scenarios in order to assess exposure requires the availability of an important number of generic parameter values. One of the key parameters in environmental assessment is the solid liquid distribution coefficient, K(d), which is used to predict radionuclide-soil interaction and subsequent radionuclide transport in the soil column. This article presents a review of K(d) values for uranium, radium, lead, polonium and thorium based on an extensive literature survey, including recent publications. The K(d) estimates were presented per soil groups defined by their texture and organic matter content (Sand, Loam, Clay and Organic), although the texture class seemed not to significantly affect K(d). Where relevant, other K(d) classification systems are proposed and correlations with soil parameters are highlighted. The K(d) values obtained in this compilation are compared with earlier review data.

Seismic Site Classification and Empirical Correlation Between Standard Penetration Test N Value and Shear Wave Velocity for Guwahati Based on Thorough Subsoil Investigation Data

NASA Astrophysics Data System (ADS)

Kumar, Abhishek; Harinarayan, N. H.; Verma, Vishal; Anand, Saurabh; Borah, Uddipana; Bania, Mousumi

2018-04-01

Guwahati, the Gateway of India in the northeast, is a large business and development center. Past seismic scenarios suggest moderate to significant effects of regional earthquakes (EQs) in Guwahati in terms of liquefaction as well as building damages. Considering the role of local soil in amplifying EQ-generated ground motions and controlling surface damages, present study attempts seismic site classification of subsoil of Guwahati. Subsoil is explored based on 43 geophysical tests and 244 borelogs gathered from different resources. Based on the borehole data, 4 numbers of 2D cross-sections are developed from different parts of Guwahati, clearly indicating that a majority of the locations are composed of clay of intermediate to high plasticity while at specific locations only, layers of sand are found at selective depths. Further, seismic site classification based on 30 m average SPT-N suggests that a major part of Guwahati falls under seismic site class (SSC) D such as Balaji Temple and Airport. However, Assam Zoo, Pan Bazaar, IIT campus, Dhol Gobinda and Maligaon show SSC E clearly indicating the presence of soft soil deposits at these locations. Similar site classification is also attempted from MASW test-based 30 m average shear wave velocity (V S30). V S30-based site classification also categorizes most of Guwahati under SSC D. However, there are locations in the southern part of Guwahati which belong to SSC C as well. Mismatch in SSC based on two different test findings for Indian soil found here are consistent with previous studies. Further, three empirical correlations based on both SPT-N and V S profiles at 22 test locations are developed for: (1) clayey; (2) sandy and (3) all soil types. Proposed correlation for all soil types is validated graphically and is found closely matching with similar correlations for Turkey and Lucknow.

Optimal land use/cover classification using remote sensing imagery for hydrological modelling in a Himalayan watershed

NASA Astrophysics Data System (ADS)

Saran, Sameer; Sterk, Geert; Kumar, Suresh

2007-10-01

Land use/cover is an important watershed surface characteristic that affects surface runoff and erosion. Many of the available hydrological models divide the watershed into Hydrological Response Units (HRU), which are spatial units with expected similar hydrological behaviours. The division into HRU's requires good-quality spatial data on land use/cover. This paper presents different approaches to attain an optimal land use/cover map based on remote sensing imagery for a Himalayan watershed in northern India. First digital classifications using maximum likelihood classifier (MLC) and a decision tree classifier were applied. The results obtained from the decision tree were better and even improved after post classification sorting. But the obtained land use/cover map was not sufficient for the delineation of HRUs, since the agricultural land use/cover class did not discriminate between the two major crops in the area i.e. paddy and maize. Therefore we adopted a visual classification approach using optical data alone and also fused with ENVISAT ASAR data. This second step with detailed classification system resulted into better classification accuracy within the 'agricultural land' class which will be further combined with topography and soil type to derive HRU's for physically-based hydrological modelling.

Mapping soil features from multispectral scanner data

NASA Technical Reports Server (NTRS)

Kristof, S. J.; Zachary, A. L.

1974-01-01

In being able to identify quickly gross variations in soil features, the computer-aided classification of multispectral scanner data can be an effective aid to soil surveying. Variations in soil tone are easily seen as well as variations in features related to soil tone, e.g., drainage patterns and organic matter content. Changes in surface texture also affect the reflectance properties of soils. Inasmuch as conventional soil classes are based on both surface and subsurface soil characteristics, the technique described here can be expected only to augment and not replace traditional soil mapping.

Atmospheric effect on classification of finite fields. [satellite-imaged agricultural areas

NASA Technical Reports Server (NTRS)

Kaufman, Y. J.; Fraser, R. S.

1984-01-01

The atmospheric effect on the upward radiance of sunlight scattered from the earth-atmosphere system is strongly influenced by the contrasts between fields and their sizes. In this paper, the radiances above finite fields are computed to simulate radiances measured by a satellite. A simulation case including 11 agricultural fields and four natural fields (water, soil, savanah, and forest) is used to test the effect of field size, background reflectance, and optical thickness of the atmosphere on the classification accuracy. For a given atmospheric turbidity, the atmospheric effect on classification of surface features may be much stronger for nonuniform surfaces than for uniform surfaces. Therefore, the classification accuracy of agricultural fields and urban areas is dependent not only on the optical characteristics of the atmosphere, but also on the size of the surface elements to be classified and their contrasts. It is concluded that new atmospheric correction methods, which take into account the finite size of the fields, are needed.

[Research progress on carbon sink function of agroforestry system under climate change].

PubMed

Xie, Ting-Ting; Su, Pei-Xi; Zhou, Zi-Juan; Shan, Li-Shan

2014-10-01

As a land comprehensive utilization system, agroforestry system can absorb and fix CO2 effectively to increase carbon storage, and also reduces greenhouse effect convincingly while reaching the aim of harvest. The regulatory role in CO2 makes humans realize that agroforestry systems have significant superiority compared with single cropping systems, therefore, understanding the carbon sinks of different components in an agroforestry system and its influencing factors play an important role in studying global carbon cycle and accurate evaluation of carbon budget. This paper reviewed the concept and classification of agroforestry system, and then the carbon sequestration potentials of different components in agroforestry systems and influencing factors. It was concluded that the carbon sequestration rate of plants from different agroforestry systems in different regions are highly variable, ranging from 0.59 to 11.08 t C · hm(-2) · a(-1), and it is mainly influenced by climatic factors and the characteristics of agroforestry systems (species composition, tree density and stand age). The soil C sequestration of any agroforestry system is influenced by the amount and quality of biomass input provided by tree and nontree components of the system and the soil properties such as soil texture and soil structure. Overall the amount of carbon storage in any agroforestry system depends on the structure and function of its each component. The future studies should focus on the carbon sink functions of structurally optimized agroforestry systems, the temporal variation and spatial distribution pattern of carbon storage in agroforestry system and its carbon sequestration mechanism in a long time.

Appendix E: Representative Pedon Descriptions for the Soils of the GLEES Wyoming Soil Survey Area: EGL, WGL & Lost Lake Watersheds

Treesearch

R. W. E. Hopper; P. M. Walthall

1994-01-01

A soil survey was conducted of the East Glacier, West Glacier and Lost Lake watersheds in July-September 1986. Procedures appropriate for an Order 3 soil survey were followed. Fifteen locations were surveyed and a total of 166 samples were analyzed. The 15 series are listed below, along with the soil classification and number of samples analyzed.

The Effect of Soil Properties on Metal Bioavailability: Field Scale Validation to Support Regulatory Acceptance

DTIC Science & Technology

2013-06-01

Bioavailability, metals, soil, bioaccessibility, ecological risk, arsenic, cadmium , chromium, lead 16. SECURITY CLASSIFICATION OF:U 17. LIMITATION...located in Sacramento, CA. Soils from a former wastewater treatment lagoon are contaminated with high concentrations of lead , chromium, and cadmium ...in soil. Soil and Sediment Contamination, 2003. 12(1): p. 1-21. 23. Pierzynski, G.M. and A.P. Schwab, Bioavailability of Zinc, Cadmium , and Lead

Classification of andisol soil on robusta coffee plantation in Silima Pungga - Pungga District

NASA Astrophysics Data System (ADS)

Marbun, P.; Nasution, Z.; Hanum, H.; Karim, A.

2018-02-01

The survey study aims to classify the Inceptisol soil on Robusta coffee plantation in Silima Pugga-Pungga District, from Order level to Sub Group level. The study was conducted on location of sample soil profiles which were determined based on Soil Map Unit (SMU) with the main Andisol Order, i.e. SMU 12, SMU 15 and SMU 17 of 18 existing SMU. The soil profiles were described to determine the morphological characteristics of the soil, while the physical and chemical properties were done by laboratory analysis. The soil samples were taken from each horizon in each profile and analyzed in the laboratory in the form of soil texture, bulk density, pH H2O, pH KCl, pH NaF, C-organic, exchangeable bases (Ca2+, Mg2+, K+, Na+), ZPC (zero point charge), base saturation, cation exchange capasity (CEC), P-retention, Al-Oxalate (Al-O) and Si-Oxalate (Si-O). The results showed that the classification of Andisol soil based on Soil Taxonomy only has one Sub Group namely Typic Hapludand. It is expected that the results of this study can provide information for more appropriate land management in order to increase the production of Robusta coffee plant in Silima Pungga-Pungga Sub district.

Integration of Landscape Ecosystem Classification and Historic Land Records in the Francis Marion National Forest

Treesearch

Peter U. Kennedy; Victor B. Shelburne

2002-01-01

Geographic Information Systems (GIS) data and historical plats ranging from 1716 to 1894 in the Coastal Flatwoods Region of South Carolina were used to quantify changes on a temporal scale. Combining the historic plats and associated witness trees (trees marking the boundaries of historic plats) with an existing database of the soils and other attributes was the basis...

Basic methods for measuring the reflectance color of iron oxides

NASA Astrophysics Data System (ADS)

Pospisil, Jaroslav; Hrdy, Jan; Hrdy Jan, Jr.

2007-06-01

The main contribution of the present article consists in coherent description and interpretation of the principles of basic measuring methods and colorimeters for color classification and evaluation of light reflecting samples containing iron oxides. The chosen relevant theoretical background is based on the CIE tristimulus colorimetric system (X,Y,Z), the CIE colorimetric system (L*,a*,b*) and the Munsell colorimetric system (H,V,C). As an example of color identification and evaluation, some specific mathematical and graphical relationships between the soil redness rate and the corresponding hematite content are shown.

Model-based classification of CPT data and automated lithostratigraphic mapping for high-resolution characterization of a heterogeneous sedimentary aquifer

PubMed Central

Mallants, Dirk; Batelaan, Okke; Gedeon, Matej; Huysmans, Marijke; Dassargues, Alain

2017-01-01

Cone penetration testing (CPT) is one of the most efficient and versatile methods currently available for geotechnical, lithostratigraphic and hydrogeological site characterization. Currently available methods for soil behaviour type classification (SBT) of CPT data however have severe limitations, often restricting their application to a local scale. For parameterization of regional groundwater flow or geotechnical models, and delineation of regional hydro- or lithostratigraphy, regional SBT classification would be very useful. This paper investigates the use of model-based clustering for SBT classification, and the influence of different clustering approaches on the properties and spatial distribution of the obtained soil classes. We additionally propose a methodology for automated lithostratigraphic mapping of regionally occurring sedimentary units using SBT classification. The methodology is applied to a large CPT dataset, covering a groundwater basin of ~60 km2 with predominantly unconsolidated sandy sediments in northern Belgium. Results show that the model-based approach is superior in detecting the true lithological classes when compared to more frequently applied unsupervised classification approaches or literature classification diagrams. We demonstrate that automated mapping of lithostratigraphic units using advanced SBT classification techniques can provide a large gain in efficiency, compared to more time-consuming manual approaches and yields at least equally accurate results. PMID:28467468

Model-based classification of CPT data and automated lithostratigraphic mapping for high-resolution characterization of a heterogeneous sedimentary aquifer.

PubMed

Rogiers, Bart; Mallants, Dirk; Batelaan, Okke; Gedeon, Matej; Huysmans, Marijke; Dassargues, Alain

2017-01-01

Cone penetration testing (CPT) is one of the most efficient and versatile methods currently available for geotechnical, lithostratigraphic and hydrogeological site characterization. Currently available methods for soil behaviour type classification (SBT) of CPT data however have severe limitations, often restricting their application to a local scale. For parameterization of regional groundwater flow or geotechnical models, and delineation of regional hydro- or lithostratigraphy, regional SBT classification would be very useful. This paper investigates the use of model-based clustering for SBT classification, and the influence of different clustering approaches on the properties and spatial distribution of the obtained soil classes. We additionally propose a methodology for automated lithostratigraphic mapping of regionally occurring sedimentary units using SBT classification. The methodology is applied to a large CPT dataset, covering a groundwater basin of ~60 km2 with predominantly unconsolidated sandy sediments in northern Belgium. Results show that the model-based approach is superior in detecting the true lithological classes when compared to more frequently applied unsupervised classification approaches or literature classification diagrams. We demonstrate that automated mapping of lithostratigraphic units using advanced SBT classification techniques can provide a large gain in efficiency, compared to more time-consuming manual approaches and yields at least equally accurate results.

7 CFR 601.1 - Functions assigned.

Code of Federal Regulations, 2013 CFR

2013-01-01

...) National Resources Inventory (NRI) that is a statistically-based survey designed and implemented using... both the provisions of the Food Security Act and Section 404 of the Clean Water Act. (ii) Soil surveys.... Soil surveys are based on scientific analysis and classification of the soils and are used to determine...

7 CFR 601.1 - Functions assigned.

Code of Federal Regulations, 2011 CFR

2011-01-01

...) National Resources Inventory (NRI) that is a statistically-based survey designed and implemented using... both the provisions of the Food Security Act and Section 404 of the Clean Water Act. (ii) Soil surveys.... Soil surveys are based on scientific analysis and classification of the soils and are used to determine...

7 CFR 601.1 - Functions assigned.

Code of Federal Regulations, 2012 CFR

2012-01-01

...) National Resources Inventory (NRI) that is a statistically-based survey designed and implemented using... both the provisions of the Food Security Act and Section 404 of the Clean Water Act. (ii) Soil surveys.... Soil surveys are based on scientific analysis and classification of the soils and are used to determine...

7 CFR 601.1 - Functions assigned.

Code of Federal Regulations, 2014 CFR

2014-01-01

...) National Resources Inventory (NRI) that is a statistically-based survey designed and implemented using... both the provisions of the Food Security Act and Section 404 of the Clean Water Act. (ii) Soil surveys.... Soil surveys are based on scientific analysis and classification of the soils and are used to determine...

7 CFR 601.1 - Functions assigned.

Code of Federal Regulations, 2010 CFR

2010-01-01

...) National Resources Inventory (NRI) that is a statistically-based survey designed and implemented using... both the provisions of the Food Security Act and Section 404 of the Clean Water Act. (ii) Soil surveys.... Soil surveys are based on scientific analysis and classification of the soils and are used to determine...

29 CFR Appendix A to Subpart P of... - Soil Classification

Code of Federal Regulations, 2010 CFR

2010-07-01

... the particles are held together by a chemical agent, such as calcium carbonate, such that a hand-size sample cannot be crushed into powder or individual soil particles by finger pressure. Cohesive soil means... quantitative and qualitative information as may be necessary to identify properly the properties, factors, and...

29 CFR Appendix B to Subpart P of... - Sloping and Benching

Code of Federal Regulations, 2013 CFR

2013-07-01

... excavations 20 feet or less in depth made in layered soils shall have a maximum allowable slope for each layer.... Distress means that the soil is in a condition where a cave-in is imminent or is likely to occur. Distress... 24 hours that an excavation is open. (c) Requirements—(1) Soil classification. Soil and rock deposits...

29 CFR Appendix B to Subpart P of... - Sloping and Benching

Code of Federal Regulations, 2012 CFR

2012-07-01

... excavations 20 feet or less in depth made in layered soils shall have a maximum allowable slope for each layer.... Distress means that the soil is in a condition where a cave-in is imminent or is likely to occur. Distress... 24 hours that an excavation is open. (c) Requirements—(1) Soil classification. Soil and rock deposits...

29 CFR Appendix B to Subpart P of... - Sloping and Benching

Code of Federal Regulations, 2014 CFR

2014-07-01

... excavations 20 feet or less in depth made in layered soils shall have a maximum allowable slope for each layer.... Distress means that the soil is in a condition where a cave-in is imminent or is likely to occur. Distress... 24 hours that an excavation is open. (c) Requirements—(1) Soil classification. Soil and rock deposits...

29 CFR Appendix B to Subpart P of... - Sloping and Benching

Code of Federal Regulations, 2011 CFR

2011-07-01

... excavations 20 feet or less in depth made in layered soils shall have a maximum allowable slope for each layer.... Distress means that the soil is in a condition where a cave-in is imminent or is likely to occur. Distress... 24 hours that an excavation is open. (c) Requirements—(1) Soil classification. Soil and rock deposits...

29 CFR Appendix B to Subpart P of... - Sloping and Benching

Code of Federal Regulations, 2010 CFR

2010-07-01

... excavations 20 feet or less in depth made in layered soils shall have a maximum allowable slope for each layer.... Distress means that the soil is in a condition where a cave-in is imminent or is likely to occur. Distress... 24 hours that an excavation is open. (c) Requirements—(1) Soil classification. Soil and rock deposits...

Integration of remote sensing (RS) and geographic information system (GIS) techniques for change detection of the land use and land cover (LULC) for soil management in the southern Port Said region, Egypt

NASA Astrophysics Data System (ADS)

Hassan, Mohamed Abd El Rehim Abd El Aziz

2014-11-01

The monitoring of land use/land cover (LULC) changes in southern Port Said region area is very important for the planner of managements, governmental and non-governmental organizations, decision makers and the scientific community. This information is essential for planning and implementing policies to optimize the use of natural resources and accommodate development whilst minimizing the impact on the environment. To monitor these changes in the study area, two sets of satellite images (Landsat TM-5 and ETM+7) data were used with Path/Row (175/38) in date 1986 and 2006, respectively. The Landsat TM and ETM data are useful for this type of study due to its high spatial resolution, spectral resolution and low repetitive acquisition (16 days). A postclassification technique is used in this study based on hybrid classification (Unsupervised and Supervised). Each method used was assessed, and checked in field. Eight to Twelve LULC classes are recognized and mapping produced. The soils in southern Port Said area were classification in two orders for soil taxonomic units, which are Entisols and Aridisols and four sub-orders classes. The study land was evaluated into five classes from non suitable (N) to very highly suitable (S1) for some crops in the southern region of Port Said studied soils, with assess the nature of future change following construction of the international coastal road which crosses near to the study area.

Soil classification for seismic site effect using MASW and ReMi methods: A case study from western Anatolia (Dikili -İzmir)

NASA Astrophysics Data System (ADS)

Karabulut, Savaş

2018-03-01

The study area is located in the northern part of Izmir, Western Turkey, prone to an active tectonic extensional regime and includes typical features of sedimentary basins, horst-grabens surrounded by a series of normal and strike-slip faults. In September 1939 the Dikili (Kabakum) earthquake with a magnitude of Mw: 6.6 occurred and after this phenomenon, residents moved from the west of Dikili to the east (i.d. soft sediments to relative to rock area). A proper estimate of the earthquake-related hazard for the area is the main objective of this study. The site effect and soil engineering problems for estimating hazard parameters at the soil surface need to be carefully analyzed for seismic site classification and geo-engineering problems like soil liquefaction, soil settlement, soil bearing capacity and soil amplification. To solve the soil static and dynamic problems, shear-wave velocities have been used in a joint interpretation process; Multichannel Analysis of Surface Waves (MASW) and Refraction Microtremor (ReMi) analyses were conducted on 121 sites with 300 × 300 m grid size in an area of 60 km2. It has been proposed that the probability of an earthquake with a magnitude of Mw: 6 occurring within 10 years is 64%, when considering the Gutenberg-Richter model. This puts the region under an important earthquake risk. The estimated Vs30 values are ≤180 m/s in the central and the northernmost part of the study area are showing an E type soil after the classification of NEHRP, where alluvial deposits are dominant. Vs30 values in the north and central part are between 180 ≤ Vs ≤ 360 m/s suggesting a D type soil. In the southernmost part of the study area where volcanic rocks are widely distributed, Vs30 values range between 360 and 908 m/s, corresponding to a C type and B type soil. The results show that soil liquefaction induced settlement and soil amplification are the most important problems in the south and the northernmost part of the study area, which is densely populated and encompasses the urbanized part of the study region.

A unified classification model for modeling of seismic liquefaction potential of soil based on CPT

PubMed Central

Samui, Pijush; Hariharan, R.

2014-01-01

The evaluation of liquefaction potential of soil due to an earthquake is an important step in geosciences. This article examines the capability of Minimax Probability Machine (MPM) for the prediction of seismic liquefaction potential of soil based on the Cone Penetration Test (CPT) data. The dataset has been taken from Chi–Chi earthquake. MPM is developed based on the use of hyperplanes. It has been adopted as a classification tool. This article uses two models (MODEL I and MODEL II). MODEL I employs Cone Resistance (qc) and Cyclic Stress Ratio (CSR) as input variables. qc and Peak Ground Acceleration (PGA) have been taken as inputs for MODEL II. The developed MPM gives 100% accuracy. The results show that the developed MPM can predict liquefaction potential of soil based on qc and PGA. PMID:26199749

A unified classification model for modeling of seismic liquefaction potential of soil based on CPT.

PubMed

Samui, Pijush; Hariharan, R

2015-07-01

The evaluation of liquefaction potential of soil due to an earthquake is an important step in geosciences. This article examines the capability of Minimax Probability Machine (MPM) for the prediction of seismic liquefaction potential of soil based on the Cone Penetration Test (CPT) data. The dataset has been taken from Chi-Chi earthquake. MPM is developed based on the use of hyperplanes. It has been adopted as a classification tool. This article uses two models (MODEL I and MODEL II). MODEL I employs Cone Resistance (q c) and Cyclic Stress Ratio (CSR) as input variables. q c and Peak Ground Acceleration (PGA) have been taken as inputs for MODEL II. The developed MPM gives 100% accuracy. The results show that the developed MPM can predict liquefaction potential of soil based on q c and PGA.

Soil Salinity Mapping in Everglades National Park Using Remote Sensing Techniques

NASA Astrophysics Data System (ADS)

Su, H.; Khadim, F. K.; Blankenship, J.; Sobhan, K.

2017-12-01

The South Florida Everglades is a vast subtropical wetland with a globally unique hydrology and ecology, and it is designated as an International Biosphere Reserve and a Wetland of International Importance. Everglades National Park (ENP) is a hydro-ecologically enriched wetland with varying salinity contents, which is a concern for terrestrial ecosystem balance and sustainability. As such, in this study, time series soil salinity mapping was carried out for the ENP area. The mapping first entailed a maximum likelihood classification of seven land cover classes for the ENP area—namely mangrove forest, mangrove scrub, low-density forest, sawgrass, prairies and marshes, barren lands with woodland hammock and water—for the years 1996, 2000, 2006, 2010 and 2015. The classifications for 1996-2010 yielded accuracies of 82%-94%, and the 2015 classification was supported through ground truthing. Afterwards, electric conductivity (EC) tolerance thresholds for each vegetation class were established,which yielded soil salinity maps comprising four soil salinity classes—i.e., the non- (EC = 0 2 dS/m), low- (EC = 2 4 dS/m), moderate- (EC = 4 8 dS/m) and high-saline (EC = >8 dS/m) areas. The soil salinity maps visualized the spatial distribution of soil salinity with no significant temporal variations. The innovative approach of "land cover identification to salinity estimation" used in the study is pragmatic and application oriented, and the study upshots are also useful, considering the diversifying ecological context of the ENP area.

Machine learning in soil classification.

PubMed

Bhattacharya, B; Solomatine, D P

2006-03-01

In a number of engineering problems, e.g. in geotechnics, petroleum engineering, etc. intervals of measured series data (signals) are to be attributed a class maintaining the constraint of contiguity and standard classification methods could be inadequate. Classification in this case needs involvement of an expert who observes the magnitude and trends of the signals in addition to any a priori information that might be available. In this paper, an approach for automating this classification procedure is presented. Firstly, a segmentation algorithm is developed and applied to segment the measured signals. Secondly, the salient features of these segments are extracted using boundary energy method. Based on the measured data and extracted features to assign classes to the segments classifiers are built; they employ Decision Trees, ANN and Support Vector Machines. The methodology was tested in classifying sub-surface soil using measured data from Cone Penetration Testing and satisfactory results were obtained.

[Object-oriented remote sensing image classification in epidemiological studies of visceral leishmaniasis in urban areas].

PubMed

Almeida, Andréa Sobral de; Werneck, Guilherme Loureiro; Resendes, Ana Paula da Costa

2014-08-01

This study explored the use of object-oriented classification of remote sensing imagery in epidemiological studies of visceral leishmaniasis (VL) in urban areas. To obtain temperature and environmental information, an object-oriented classification approach was applied to Landsat 5 TM scenes from the city of Teresina, Piauí State, Brazil. For 1993-1996, VL incidence rates correlated positively with census tracts covered by dense vegetation, grass/pasture, and bare soil and negatively with areas covered by water and densely populated areas. In 2001-2006, positive correlations were found with dense vegetation, grass/pasture, bare soil, and densely populated areas and negative correlations with occupied urban areas with some vegetation. Land surface temperature correlated negatively with VL incidence in both periods. Object-oriented classification can be useful to characterize landscape features associated with VL in urban areas and to help identify risk areas in order to prioritize interventions.

Uptake of 137Cs by Leafy Vegetables and Grains from Calcareous Soils

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robison, W; Hamilton, T; Conrado, C

2004-04-19

Cesium-137 was deposited on Bikini Island at Bikini Atoll in 1954 as a result of nuclear testing and has been transported and cycled in the ecosystem ever since. Atoll soils are of marine origin and are almost pure CaCO{sub 3} with high concentrations of organic matter in the top 40 cm. Data from previous experiments with mature fruit trees show very high transfer factors (TF's), [Bq g{sup -1} plant/ Bq g{sup -1} soil, both in dry weight] into fruits from atoll calcareous soil. These TF's are much higher than reported for continental, silica-based soils. In this report TF's for 5more » types of leafy vegetable crops and 2 types of grain crops are provided for use in predictive dose assessments and for comparison with other data from other investigators working with other types of soil in the IAEA CRP ''The Classification of Soil Systems on the Basis of Transfer Factors of Radionuclides from Soil to Reference Plants''. Transfer factors for plants grown on calcareous soil are again very high relative to clay-containing soils and range from 23 to 39 for grain crops and 21 to 113 for leafy vegetables. Results from these experiments, in this unique, high pH, high organic content, low potassium (K) soil, provide a boundary condition for models relating soil properties to TF.« less

One perspective on spatial variability in geologic mapping

USGS Publications Warehouse

Markewich, H.W.; Cooper, S.C.

1991-01-01

This paper discusses some of the differences between geologic mapping and soil mapping, and how the resultant maps are interpreted. The role of spatial variability in geologic mapping is addressed only indirectly because in geologic mapping there have been few attempts at quantification of spatial differences. This is largely because geologic maps deal with temporal as well as spatial variability and consider time, age, and origin, as well as composition and geometry. Both soil scientists and geologists use spatial variability to delineate mappable units; however, the classification systems from which these mappable units are defined differ greatly. Mappable soil units are derived from systematic, well-defined, highly structured sets of taxonomic criteria; whereas mappable geologic units are based on a more arbitrary heirarchy of categories that integrate many features without strict values or definitions. Soil taxonomy is a sorting tool used to reduce heterogeneity between soil units. Thus at the series level, soils in any one series are relatively homogeneous because their range of properties is small and well-defined. Soil maps show the distribution of soils on the land surface. Within a map area, soils, which are often less than 2 m thick, show a direct correlation to topography and to active surface processes as well as to parent material.

[Review on water eco-environment in vegetation restoration in Loess Plateau].

PubMed

Hu, Liangjun; Shao, Mingan

2002-08-01

Water is the crucial factor influencing vegetation restoration and eco-environmental reconstruction in Loess Plateau region. In this paper, the previous studies on water eco-environment under vegetation construction were summarized from seven aspects, i.e., soil water resource, background of soil water, dynamics of soil water, dry soil layer, relationship between soil water and vegetarian productivity, classification of soil water position, and strategy for vegetation construction. Meanwhile, some problems in the relevant researches were pointed out and discussed.

The Influence of Processing Soil With a Coffee Grinder on Soil Classification

DTIC Science & Technology

2015-01-20

shaker, sieves , coffee grinder, plastic limit tool, bowls, spatulas, and scoops. To classify soils, a dry sieve analysis is performed, as is a Plastic...processed with the coffee grinder for 90 seconds as described above. Sieve analysis using the wet preparation method was used to test and classify the soils...one 90 second cycle of Elevator Soil Figure 3: The blades after three 90 second cycles of Elevator Soil 71Page 4.2 Ottawa Sand Dry Sieve Analysis

Effects of Freezing and Thawing on Consolidation Behavior of Clayey Soils

NASA Astrophysics Data System (ADS)

Binal, Adil; Adeli, Parisa

2015-04-01

An apprehending of freezing and thawing effects on cohesive soil is considerable for many construction and environmental subjects. This paper relates the effects of freezing and thawing on consolidation behaviour of clayey soils. The Capital of Ankara settled on a sequence of lacustrine sediments. These sediments include fine grain soils, locally. Collected samples were undisturbed grey clay and clayey sand that were obtained from the bottom of a construction zone at about 1m depth below the ground surface. Total of 32 moulded samples were prepared with constant water content to reflect the moisture condition in the active surface layer. Gray clay and clayey sand were analysed in the laboratory, and found to have the plastic limits (PL) of 33.01% and 22.56%, the liquid limits (LL) of 75.05% and 36.97%, and the plasticity indexes (PI) of 42.04% and 14.41%. The soil samples were classified as "CH" and "SC" in accordance with the unified soil classification system. Soil samples for all tests were placed in a freezer that has -18°C temperature. Samples have been waited in it for twenty-four hours. Then, they have been removed from the freezer and allowed to stand for twenty-four hours at a constant room temperature (21°C) and humidity (80% RH). As a result, one freezing and thawing cycle was achieved between -18°C (24 hours) and 21°C (24 hours), and it took two days. Freezing and thawing (FT) sequences were selected as 1, 3, 7, 14 and 21. After each FT sequence, Atterberg limits and consolidation tests were carried out in accordance with ASTM standards. Liquid and plastic limits of soil samples, suddenly, were decreased after first FT cycle. That state is a sign of the clay mineral orientation due to freezing and thawing process. The soil classification of clayey sand was changed from "SC" to "SM" after first FT cycle. Furthermore, the coefficient of consolidation and permeability of grey clay had been increased by rising in FT cycles up to 7 and then continue to decline as well as these values of clayey sand start to decrease after 14 FT cycles.

Subsurface event detection and classification using Wireless Signal Networks.

PubMed

Yoon, Suk-Un; Ghazanfari, Ehsan; Cheng, Liang; Pamukcu, Sibel; Suleiman, Muhannad T

2012-11-05

Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs). The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events.

Subsurface Event Detection and Classification Using Wireless Signal Networks

PubMed Central

Yoon, Suk-Un; Ghazanfari, Ehsan; Cheng, Liang; Pamukcu, Sibel; Suleiman, Muhannad T.

2012-01-01

Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs). The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events. PMID:23202191

Application of remote sensing technology to the solution of problems in the management of resources in Indiana

NASA Technical Reports Server (NTRS)

Weismiller, R. A.; Mroczynski, R. P. (Principal Investigator)

1977-01-01

The author has identified the following significant results. The Lydick, South Bend West, South Bend East, and Osceola quadrangles were successfully classified into twenty-six cover types with a high degree of accuracy. The ability of this computer-assisted classification system to delineate various stages of urban development, from heavy industry to new suburban development, was of particular interest to the planning commission. The classification is clearly more beneficial than the existing agricultural soils and topographic maps, because it shows the current ground cover conditions all on one map. It shows how an area is developing along with the specific type and location of new development. The classification also shows at a glance whether development is taking place in an area suitable for development or if growth is taking place in prime agricultural land, areas of poor foundation material, or other places where development is not desirable.

Variability of the soil-to-plant radiocaesium transfer factor for Japanese soils predicted with soil and plant properties.

PubMed

Uematsu, Shinichiro; Vandenhove, Hildegarde; Sweeck, Lieve; Van Hees, May; Wannijn, Jean; Smolders, Erik

2016-03-01

Food chain contamination with radiocaesium (RCs) in the aftermath of the Fukushima accident calls for an analysis of the specific factors that control the RCs transfer. Here, soil-to-plant transfer factors (TF) of RCs for grass were predicted from the potassium concentration in soil solution (mK) and the Radiocaesium Interception Potential (RIP) of the soil using existing mechanistic models. The mK and RIP were (a) either measured for 37 topsoils collected from the Fukushima accident affected area or (b) predicted from the soil clay content and the soil exchangeable potassium content using the models that had been calibrated for European soils. An average ammonium concentration was used throughout in the prediction. The measured RIP ranged 14-fold and measured mK varied 37-fold among the soils. The measured RIP was lower than the RIP predicted from the soil clay content likely due to the lower content of weathered micas in the clay fraction of Japanese soils. Also the measured mK was lower than that predicted. As a result, the predicted TFs relying on the measured RIP and mK were, on average, about 22-fold larger than the TFs predicted using the European calibrated models. The geometric mean of the measured TFs for grass in the affected area (N = 82) was in the middle of both. The TFs were poorly related to soil classification classes, likely because soil fertility (mK) was obscuring the effects of the soil classification related to the soil mineralogy (RIP). This study suggests that, on average, Japanese soils are more vulnerable than European soils at equal soil clay and exchangeable K content. The affected regions will be targeted for refined model validation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Protocol for Cohesionless Sample Preparation for Physical Experimentation

DTIC Science & Technology

2016-05-01

protocol for specimen preparation that will enable the use of soil strength curves based on expedient field classification testing (e.g., grain-size...void ratio and relative compaction, which compares field compaction to a laboratory maximum density. Gradation charts for the two materials used in...the failure stress. Ring shear testing was performed using the GCTS Residual-Ring Shear System SRS-150 in order to measure the peak torsional

Review and Future Research Directions about Major Monitoring Method of Soil Erosion

NASA Astrophysics Data System (ADS)

LI, Yue; Bai, Xiaoyong; Tian, Yichao; Luo, Guangjie

2017-05-01

Soil erosion is a highly serious ecological problem that occurs worldwide. Hence,scientific methods for accurate monitoring are needed to obtain soil erosion data. At present,numerous methods on soil erosion monitoring are being used internationally. In this paper, wepresent a systematic classification of these methods based on the date of establishment andtype of approach. This classification comprises five categories: runoff plot method, erosion pinmethod, radionuclide tracer method, model estimation, and 3S technology combined method.The backgrounds of their establishment are briefly introduced, the history of their developmentis reviewed, and the conditions for their application are enumerated. Their respectiveadvantages and disadvantages are compared and analysed, and future prospects regarding theirdevelopment are discussed. We conclude that the methods of soil erosion monitoring in the past 100 years of their development constantly considered the needs of the time. According to the progress of soil erosion monitoring technology throughout its history, we predict that the future trend in this field would move toward the development of quantitative, precise, and composite methods. This report serves as a valuable reference for scientific and technological workers globally, especially those engaged in soil erosion research.

Spectral signature selection for mapping unvegetated soils

NASA Technical Reports Server (NTRS)

May, G. A.; Petersen, G. W.

1975-01-01

Airborne multispectral scanner data covering the wavelength interval from 0.40-2.60 microns were collected at an altitude of 1000 m above the terrain in southeastern Pennsylvania. Uniform training areas were selected within three sites from this flightline. Soil samples were collected from each site and a procedure developed to allow assignment of scan line and element number from the multispectral scanner data to each sampling location. These soil samples were analyzed on a spectrophotometer and laboratory spectral signatures were derived. After correcting for solar radiation and atmospheric attenuation, the laboratory signatures were compared to the spectral signatures derived from these same soils using multispectral scanner data. Both signatures were used in supervised and unsupervised classification routines. Computer-generated maps using the laboratory and multispectral scanner derived signatures resulted in maps that were similar to maps resulting from field surveys. Approximately 90% agreement was obtained between classification maps produced using multispectral scanner derived signatures and laboratory derived signatures.

Influence of Long-term Application of Feedlot Manure Amendments on Water Repellency of a Clay Loam Soil.

PubMed

Miller, Jim J; Beasley, Bruce W; Hazendonk, Paul; Drury, Craig F; Chanasyk, David S

2017-05-01

Long-term application of feedlot manure to cropland may increase the quantity of soil organic carbon (C) and change its quality, which may influence soil water repellency. The objective was to determine the influence of feedlot manure type (stockpiled vs. composted), bedding material (straw [ST] vs. woodchips [WD]), and application rate (13, 39, or 77 Mg ha) on repellency of a clay loam soil after 17 annual applications. The repellency was determined on all 14 treatments using the water repellency index ( index), the water drop penetration time (WDPT) method, and molarity of ethanol (MED) test. The C composition of particulate organic matter in soil of five selected treatments after 16 annual applications was also determined using C nuclear magnetic resonance-direct polarization with magic-angle spinning (NMR-DPMAS). Manure type had no significant ( > 0.05) effect on index and WDPT, and MED classification was similar. Mean index and WDPT values were significantly greater and MED classification more hydrophobic for WD than ST. Application rate had no effect on the index, but WDPT was significantly greater and MED classification more hydrophobic with increasing application rate. Strong ( > 0.7) but nonsignificant positive correlations were found between index and WDPT versus hydrophobic (alkyl + aromatic) C, lignin at 74 ppm (O-alkyl), and unspecified aromatic compounds at 144 ppm. Specific aromatic compounds also contributed more to repellency than alkyl, O-alkyl, and carbonyl compounds. Overall, all three methods consistently showed that repellency was greater for WD- than ST-amended clay loam soil, but manure type had no effect. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

STIR Proposal For Research Area 2.1.2 Surface Energy Balance: Transient Soil Density Impacts Land Surface Characteristics and Characterization

DTIC Science & Technology

2015-12-22

not shown). The relatively small differences were likely associated with differences in surface albedo and longwave radiation from soil surface. Ground...SECURITY CLASSIFICATION OF: Soil density is commonly treated as static in studies on land surface property dynamics. Magnitudes of errors associated...with this assumption are largely unknown. Objectives of this preliminary investigation were to: i) quantify effects of soil density variation on soil

Local Climate Zones Classification to Urban Planning in the Mega City of São Paulo - SP, Brazil

NASA Astrophysics Data System (ADS)

Gonçalves Santos, Rafael; Saraiva Lopes, António Manuel; Prata-Shimomura, Alessandra

2017-04-01

Local Climate Zones Classification to Urban Planning in the Mega city of São Paulo - SP, Brazil Tropical megacities have presented a strong trend in growing urban. Urban management in megacities has as one of the biggest challenges is the lack of integration of urban climate and urban planning to promote ecologically smart cities. Local Climatic Zones (LCZs) are considered as important and recognized tool for urban climate management. Classes are local in scale, climatic in nature, and zonal in representation. They can be understood as regions of uniform surface cover, structure, material and human activity that have to a unique climate response. As an initial tool to promote urban climate planning, LCZs represent a simple composition of different land coverages (buildings, vegetation, soils, rock, roads and water). LCZs are divided in 17 classes, they are based on surface cover (built fraction, soil moisture, albedo), surface structure (sky view factor, roughness height) and cultural activity (anthropogenic heat flux). The aim of this study is the application of the LCZs classification system in the megacity of São Paulo, Brazil. Located at a latitude of 23° 21' and longitude 46° 44' near to the Tropic of Capricorn, presenting humid subtropical climate (Cfa) with diversified topographies. The megacity of São Paulo currently concentrates 11.890.000 inhabitants is characterized by large urban conglomerates with impermeable surfaces and high verticalization, having as result high urban heat island intensity. The result indicates predominance in urban zones of Compact low-rise, Compact Mid-rise, Compact High-rise and Open Low-rise. Non-urban regions are mainly covered by dense vegetation and water. The LCZs classification system promotes significant advantages for climate sensitive urban planning in the megacity of São Paulo. They offers new perspectives to the management of temperature and urban ventilation and allows the formulation of urban planning guidelines and climatic. Key words: Local Climatic Zones; Urban Panning; Megacities; São Paulo.

Reduction of Topographic Effect for Curve Number Estimated from Remotely Sensed Imagery

NASA Astrophysics Data System (ADS)

Zhang, Wen-Yan; Lin, Chao-Yuan

2016-04-01

The Soil Conservation Service Curve Number (SCS-CN) method is commonly used in hydrology to estimate direct runoff volume. The CN is the empirical parameter which corresponding to land use/land cover, hydrologic soil group and antecedent soil moisture condition. In large watersheds with complex topography, satellite remote sensing is the appropriate approach to acquire the land use change information. However, the topographic effect have been usually found in the remotely sensed imageries and resulted in land use classification. This research selected summer and winter scenes of Landsat-5 TM during 2008 to classified land use in Chen-You-Lan Watershed, Taiwan. The b-correction, the empirical topographic correction method, was applied to Landsat-5 TM data. Land use were categorized using K-mean classification into 4 groups i.e. forest, grassland, agriculture and river. Accuracy assessment of image classification was performed with national land use map. The results showed that after topographic correction, the overall accuracy of classification was increased from 68.0% to 74.5%. The average CN estimated from remotely sensed imagery decreased from 48.69 to 45.35 where the average CN estimated from national LULC map was 44.11. Therefore, the topographic correction method was recommended to normalize the topographic effect from the satellite remote sensing data before estimating the CN.

Soil indigenous knowledge in North Central Namibia

NASA Astrophysics Data System (ADS)

Prudat, Brice; Bloemertz, Lena; Kuhn, Nikolaus J.

2016-04-01

Mapping and classifying soils is part of an important learning process to improve soil management practices, soil quality and increase productivity. In order to assess soil quality improvement related to an ongoing land reform in North-Central Namibia, the characteristics that determine soil quality in the local land use context were determined in this study. To do so, we collated the indigenous soil knowledge in North-Central Namibia where the Ovakwanyama cultivate pearl millet for centuries. Local soil groups are defined mostly based on their productivity potential, which varies depending on the rainfall pattern. The morphological criteria used by the farmers to differentiate the soil groups (colour, consistence) were supported by a conventional analysis of soil physical and chemical properties. Now, they can be used to develop a soil quality assessment toolbox adapted to the regional use. The characteristics of the tool box do not directly indicate soil quality, but refer to local soils groups. The quality of these groups is relatively homogenous at the local scale. Our results show that understanding of indigenous soil knowledge has great potential to improve soil quality assessment with regards to land use. The integration of this knowledge with the conventional soil analysis improves the local meaning of such a "scientific" assessment and thus facilitates dialog between farmers and agronomists, but also scientists working in different regions of the world, but in similar conditions. Overall, the integration of indigenous knowledge in international classification systems (e.g. WRB) as attempted in this study has thus a major potential to improve soil mapping in the local context.

Recognizing Banknote Fitness with a Visible Light One Dimensional Line Image Sensor

PubMed Central

Pham, Tuyen Danh; Park, Young Ho; Kwon, Seung Yong; Nguyen, Dat Tien; Vokhidov, Husan; Park, Kang Ryoung; Jeong, Dae Sik; Yoon, Sungsoo

2015-01-01

In general, dirty banknotes that have creases or soiled surfaces should be replaced by new banknotes, whereas clean banknotes should be recirculated. Therefore, the accurate classification of banknote fitness when sorting paper currency is an important and challenging task. Most previous research has focused on sensors that used visible, infrared, and ultraviolet light. Furthermore, there was little previous research on the fitness classification for Indian paper currency. Therefore, we propose a new method for classifying the fitness of Indian banknotes, with a one-dimensional line image sensor that uses only visible light. The fitness of banknotes is usually determined by various factors such as soiling, creases, and tears, etc. although we just consider banknote soiling in our research. This research is novel in the following four ways: first, there has been little research conducted on fitness classification for the Indian Rupee using visible-light images. Second, the classification is conducted based on the features extracted from the regions of interest (ROIs), which contain little texture. Third, 1-level discrete wavelet transformation (DWT) is used to extract the features for discriminating between fit and unfit banknotes. Fourth, the optimal DWT features that represent the fitness and unfitness of banknotes are selected based on linear regression analysis with ground-truth data measured by densitometer. In addition, the selected features are used as the inputs to a support vector machine (SVM) for the final classification of banknote fitness. Experimental results showed that our method outperforms other methods. PMID:26343654

Characterisation of the Permafrost Carbon Pool

USGS Publications Warehouse

Kuhry, P.; Grosse, G.; Harden, J.W.; Hugelius, G.; Koven, C.D.; Ping, C.-L.; Schirrmeister, L.; Tarnocai, C.

2013-01-01

The current estimate of the soil organic carbon (SOC) pool in the northern permafrost region of 1672 Petagrams (Pg) C is much larger than previously reported and needs to be incorporated in global soil carbon (C) inventories. The Northern Circumpolar Soil Carbon Database (NCSCD), extended to include the range 0–300 cm, is now available online for wider use by the scientific community. An important future aim is to provide quantitative uncertainty ranges for C pool estimates. Recent studies have greatly improved understanding of the regional patterns, landscape distribution and vertical (soil horizon) partitioning of the permafrost C pool in the upper 3 m of soils. However, the deeper C pools in unconsolidated Quaternary deposits need to be better constrained. A general lability classification of the permafrost C pool should be developed to address potential C release upon thaw. The permafrost C pool and its dynamics are beginning to be incorporated into Earth System models, although key periglacial processes such as thermokarst still need to be properly represented to obtain a better quantification of the full permafrost C feedback on global climate change.

An integrated Landsat/ancillary data classification of desert rangeland

NASA Technical Reports Server (NTRS)

Price, K. P.; Ridd, M. K.; Merola, J. A.

1985-01-01

Range inventorying methods using Landsat MSS data, coupled with ancillary data were examined. The study area encompassed nearly 20,000 acres in Rush Valley, UT. The vegetation is predominately desert shrub and annual grasses, with same annual forbs. Three Landsat scenes were evaluated using a Kauth-Thomas brightness/greenness data transformation (May, June, and August dates). The data was classified using a four-band maximum-likelihood classifier. A print map was taken into the field to determine the relationship between print symbols and vegetation. It was determined that classification confusion could be greatly reduced by incorporating geomorphic units and soil texture (coarse vs fine) into the classification. Spectral data, geomorphic units, and soil texture were combined in a GIS format to produce a final vegetation map identifying 12 vegetation types.

An integrated LANDSAT/ancillary data classification of desert rangeland

NASA Technical Reports Server (NTRS)

Price, K. P.; Ridd, M. K.; Merola, J. A.

1984-01-01

Range inventorying methods using LANDSAT MSS data, coupled with ancillary data were examined. The study area encompassed nearly 20,000 acres in Rush Valley, Utah. The vegetation is predominately desert shrub and annual grasses, with some annual forbs. Three LANDSAT scenes were evaluated using a Kauth-Thomas brightness/greenness data transformation (May, June, and August dates). The data was classified using a four-band maximum-likelihood classifier. A print map was taken into the field to determine the relationship between print symbols and vegetation. It was determined that classification confusion could be greatly reduced by incorporating geomorphic units and soil texture (coarse vs fine) into the classification. Spectral data, geomorphic units, and soil texture were combined in a GIS format to produce a final vegetation map identifying 12 vegetation types.

Forest management applications of Landsat data in a geographic information system

NASA Technical Reports Server (NTRS)

Maw, K. D.; Brass, J. A.

1982-01-01

The utility of land-cover data resulting from Landsat MSS classification can be greatly enhanced by use in combination with ancillary data. A demonstration forest management applications data base was constructed for Santa Cruz County, California, to demonstrate geographic information system applications of classified Landsat data. The data base contained detailed soils, digital terrain, land ownership, jurisdictional boundaries, fire events, and generalized land-use data, all registered to a UTM grid base. Applications models were developed from problems typical of fire management and reforestation planning.

The stability of clay using mount Sinabung ash with unconfined compression test (uct) value

NASA Astrophysics Data System (ADS)

Puji Hastuty, Ika; Roesyanto; Hutauruk, Ronny; Simanjuntak, Oberlyn

2018-03-01

The soil has a important role as a highway’s embankment material (sub grade). Soil conditions are very different in each location because the scientifically soil is a very complex and varied material and the located on the field is very loose or very soft, so it is not suitable for construction, then the soil should be stabilized. The additive material commonly used for soil stabilization includes cement, lime, fly ash, rice husk ash, and others. This experiment is using the addition of volcanic ash. The purpose of this study was to determine the Index Properties and Compressive Strength maximum value with Unconfined Compression Test due to the addition of volcanic ash as a stabilizing agent along with optimum levels of the addition. The result showed that the original soil sample has Water Content of 14.52%; the Specific Weight of 2.64%; Liquid limit of 48.64% and Plasticity Index of 29.82%. Then, the Compressive Strength value is 1.40 kg/cm2. According to USCS classification, the soil samples categorized as the (CL) type while based on AASHTO classification, the soil samples are including as the type of A-7-6. After the soil is stabilized with a variety of volcanic ash, can be concluded that the maximum value occurs at mixture variation of 11% Volcanic Ash with Unconfined Compressive Strength value of 2.32 kg/cm2.

Benefit assessment of soil and water conservation from cropland to forest in hilly Loess Plateau at Qinghai.

PubMed

Zhao, Chuanchuan; Yang, Ninggui; Wang, Zhen; Liu, Sili; Dong, Xu; Xin, Wenrong

2013-01-01

The information of slope and vegetation coverage of the monitoring region were extracted, based on DEM (Digital Evaluation Model) and Spot5 Satellite data images, and fishnet grid was generated using GIS (Geographic Information System) and RS (Remote Sensing) technique. Applying the information of slop and vegetation coverage layers into the corresponding space grid by using the function of zonal statistics and analysis, it can realize overlay analysis based on Standards for Classification and Gradation of Soil Erosion (SL190-2007), and obtains the map of soil erosion intensity of the monitoring region. Finally, according to Specifications for Assessment of Forest Ecosystem Services (LY/T1721-2008) and monitoring data of typical plot, the soil and water conservation value from cropland to forest was evaluated quantitatively in 2009. The results showed that the area, on and below the moderate level, was 93600 ha, taking up 50.03% of total conversion of farmland to forest area (185100 ha), which indicates a 14.64 million (t/a) of soil conversion, and a 1520 million Yuan for erosion control. The results of the study showed that the soil and water conservation was very effective.

Helping People Understand Soils - Perspectives from the US National Cooperative Soil Survey

NASA Astrophysics Data System (ADS)

Reich, Paul; Cheever, Tammy; Greene, Linda; Southard, Susan; Levin, Maxine; Lindbo, David L.; Monger, Curtis

2017-04-01

Throughout the history of the US National Cooperative Soil Survey (NCSS), soil science education has been a part of the mission to better understand one of our most precious natural resources: the Soil. The poster will highlight the many products and programs related to soils that USDA NRCS (soils.usda.gov) has developed over the years for K-12 and college/professional education. NRCS scientific publications covering topics on soil properties, soil classification, soil health and soil quality have become an important part of the university soil science curriculum. Classroom lesson plans and grade appropriate materials help K-12 teachers introduce soil concepts to students and include detailed instructions and materials for classroom demonstrations of soil properties. A Handbook for Collegiate Soils Contests support universities that conduct Collegiate Soil Judging contests.

Use of data mining techniques to classify soil CO2 emission induced by crop management in sugarcane field.

PubMed

Farhate, Camila Viana Vieira; Souza, Zigomar Menezes de; Oliveira, Stanley Robson de Medeiros; Tavares, Rose Luiza Moraes; Carvalho, João Luís Nunes

2018-01-01

Soil CO2 emissions are regarded as one of the largest flows of the global carbon cycle and small changes in their magnitude can have a large effect on the CO2 concentration in the atmosphere. Thus, a better understanding of this attribute would enable the identification of promoters and the development of strategies to mitigate the risks of climate change. Therefore, our study aimed at using data mining techniques to predict the soil CO2 emission induced by crop management in sugarcane areas in Brazil. To do so, we used different variable selection methods (correlation, chi-square, wrapper) and classification (Decision tree, Bayesian models, neural networks, support vector machine, bagging with logistic regression), and finally we tested the efficiency of different approaches through the Receiver Operating Characteristic (ROC) curve. The original dataset consisted of 19 variables (18 independent variables and one dependent (or response) variable). The association between cover crop and minimum tillage are effective strategies to promote the mitigation of soil CO2 emissions, in which the average CO2 emissions are 63 kg ha-1 day-1. The variables soil moisture, soil temperature (Ts), rainfall, pH, and organic carbon were most frequently selected for soil CO2 emission classification using different methods for attribute selection. According to the results of the ROC curve, the best approaches for soil CO2 emission classification were the following: (I)-the Multilayer Perceptron classifier with attribute selection through the wrapper method, that presented rate of false positive of 13,50%, true positive of 94,20% area under the curve (AUC) of 89,90% (II)-the Bagging classifier with logistic regression with attribute selection through the Chi-square method, that presented rate of false positive of 13,50%, true positive of 94,20% AUC of 89,90%. However, the (I) approach stands out in relation to (II) for its higher positive class accuracy (high CO2 emission) and lower computational cost.

Use of data mining techniques to classify soil CO2 emission induced by crop management in sugarcane field

PubMed Central

de Souza, Zigomar Menezes; Oliveira, Stanley Robson de Medeiros; Tavares, Rose Luiza Moraes; Carvalho, João Luís Nunes

2018-01-01

Soil CO2 emissions are regarded as one of the largest flows of the global carbon cycle and small changes in their magnitude can have a large effect on the CO2 concentration in the atmosphere. Thus, a better understanding of this attribute would enable the identification of promoters and the development of strategies to mitigate the risks of climate change. Therefore, our study aimed at using data mining techniques to predict the soil CO2 emission induced by crop management in sugarcane areas in Brazil. To do so, we used different variable selection methods (correlation, chi-square, wrapper) and classification (Decision tree, Bayesian models, neural networks, support vector machine, bagging with logistic regression), and finally we tested the efficiency of different approaches through the Receiver Operating Characteristic (ROC) curve. The original dataset consisted of 19 variables (18 independent variables and one dependent (or response) variable). The association between cover crop and minimum tillage are effective strategies to promote the mitigation of soil CO2 emissions, in which the average CO2 emissions are 63 kg ha-1 day-1. The variables soil moisture, soil temperature (Ts), rainfall, pH, and organic carbon were most frequently selected for soil CO2 emission classification using different methods for attribute selection. According to the results of the ROC curve, the best approaches for soil CO2 emission classification were the following: (I)–the Multilayer Perceptron classifier with attribute selection through the wrapper method, that presented rate of false positive of 13,50%, true positive of 94,20% area under the curve (AUC) of 89,90% (II)–the Bagging classifier with logistic regression with attribute selection through the Chi-square method, that presented rate of false positive of 13,50%, true positive of 94,20% AUC of 89,90%. However, the (I) approach stands out in relation to (II) for its higher positive class accuracy (high CO2 emission) and lower computational cost. PMID:29513765

A classification model of Hyperion image base on SAM combined decision tree

NASA Astrophysics Data System (ADS)

Wang, Zhenghai; Hu, Guangdao; Zhou, YongZhang; Liu, Xin

2009-10-01

Monitoring the Earth using imaging spectrometers has necessitated more accurate analyses and new applications to remote sensing. A very high dimensional input space requires an exponentially large amount of data to adequately and reliably represent the classes in that space. On the other hand, with increase in the input dimensionality the hypothesis space grows exponentially, which makes the classification performance highly unreliable. Traditional classification algorithms Classification of hyperspectral images is challenging. New algorithms have to be developed for hyperspectral data classification. The Spectral Angle Mapper (SAM) is a physically-based spectral classification that uses an ndimensional angle to match pixels to reference spectra. The algorithm determines the spectral similarity between two spectra by calculating the angle between the spectra, treating them as vectors in a space with dimensionality equal to the number of bands. The key and difficulty is that we should artificial defining the threshold of SAM. The classification precision depends on the rationality of the threshold of SAM. In order to resolve this problem, this paper proposes a new automatic classification model of remote sensing image using SAM combined with decision tree. It can automatic choose the appropriate threshold of SAM and improve the classify precision of SAM base on the analyze of field spectrum. The test area located in Heqing Yunnan was imaged by EO_1 Hyperion imaging spectrometer using 224 bands in visual and near infrared. The area included limestone areas, rock fields, soil and forests. The area was classified into four different vegetation and soil types. The results show that this method choose the appropriate threshold of SAM and eliminates the disturbance and influence of unwanted objects effectively, so as to improve the classification precision. Compared with the likelihood classification by field survey data, the classification precision of this model heightens 9.9%.

Optimal land use/land cover classification using remote sensing imagery for hydrological modeling in a Himalayan watershed

NASA Astrophysics Data System (ADS)

Saran, Sameer; Sterk, Geert; Kumar, Suresh

2009-10-01

Land use/land cover is an important watershed surface characteristic that affects surface runoff and erosion. Many of the available hydrological models divide the watershed into Hydrological Response Units (HRU), which are spatial units with expected similar hydrological behaviours. The division into HRU's requires good-quality spatial data on land use/land cover. This paper presents different approaches to attain an optimal land use/land cover map based on remote sensing imagery for a Himalayan watershed in northern India. First digital classifications using maximum likelihood classifier (MLC) and a decision tree classifier were applied. The results obtained from the decision tree were better and even improved after post classification sorting. But the obtained land use/land cover map was not sufficient for the delineation of HRUs, since the agricultural land use/land cover class did not discriminate between the two major crops in the area i.e. paddy and maize. Subsequently the digital classification on fused data (ASAR and ASTER) were attempted to map land use/land cover classes with emphasis to delineate the paddy and maize crops but the supervised classification over fused datasets did not provide the desired accuracy and proper delineation of paddy and maize crops. Eventually, we adopted a visual classification approach on fused data. This second step with detailed classification system resulted into better classification accuracy within the 'agricultural land' class which will be further combined with topography and soil type to derive HRU's for physically-based hydrological modeling.

Mapping soil texture classes and optimization of the result by accuracy assessment

NASA Astrophysics Data System (ADS)

Laborczi, Annamária; Takács, Katalin; Bakacsi, Zsófia; Szabó, József; Pásztor, László

2014-05-01

There are increasing demands nowadays on spatial soil information in order to support environmental related and land use management decisions. The GlobalSoilMap.net (GSM) project aims to make a new digital soil map of the world using state-of-the-art and emerging technologies for soil mapping and predicting soil properties at fine resolution. Sand, silt and clay are among the mandatory GSM soil properties. Furthermore, soil texture class information is input data of significant agro-meteorological and hydrological models. Our present work aims to compare and evaluate different digital soil mapping methods and variables for producing the most accurate spatial prediction of texture classes in Hungary. In addition to the Hungarian Soil Information and Monitoring System as our basic data, digital elevation model and its derived components, geological database, and physical property maps of the Digital Kreybig Soil Information System have been applied as auxiliary elements. Two approaches have been applied for the mapping process. At first the sand, silt and clay rasters have been computed independently using regression kriging (RK). From these rasters, according to the USDA categories, we have compiled the texture class map. Different combinations of reference and training soil data and auxiliary covariables have resulted several different maps. However, these results consequentially include the uncertainty factor of the three kriged rasters. Therefore we have suited data mining methods as the other approach of digital soil mapping. By working out of classification trees and random forests we have got directly the texture class maps. In this way the various results can be compared to the RK maps. The performance of the different methods and data has been examined by testing the accuracy of the geostatistically computed and the directly classified results. We have used the GSM methodology to assess the most predictive and accurate way for getting the best among the several result maps. Acknowledgement: Our work was supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).

Seeing the soil through the net: an eye-opener on the soil map of the Flemish region (Belgium)

NASA Astrophysics Data System (ADS)

Dondeyne, Stefaan; Vanierschot, Laura; Langohr, Roger; Van Ranst, Eric; Deckers, Jozef; Oorts, Katrien

2017-04-01

A systematic soil survey of Belgium was conducted from 1948 to 1991. Field surveys were done at the detailed scale of 1:5000 with the final maps published at a 1:20,000 scale. The legend of these detailed soil maps (scale 1:20,000) has been converted to the 3rd edition of the international soil classification system 'World Reference Base for Soil Resources' (WRB). Over the last years, the government of the Flemish region made great efforts to make these maps, along with other environmental data, available to the general audience through the internet. The soil maps are widely used and consulted by researchers, teachers, land-use planners, environmental consultancy agencies and archaeologists. The maps can be downloaded and consulted in the viewer 'Visual Soil Explorer' ('Bodemverkenner'). To increase the legibility of the maps, we assembled a collection of photographs from soil profiles representing 923 soil types and 413 photos of related landscape settings. By clicking on a specific location in the 'Visual Soil Explorer', pictures of the corresponding soil type and landscape appear in a pop-up window, with a brief explanation about the soil properties. The collection of photographs of soil profiles cover almost 80% of the total area of the Flemish region, and include the 100 most common soil types. Our own teaching experience shows that these information layers are particular valuable for teaching soil geography and earth sciences in general. Overall, such visual information layers should contribute to a better interpretation of the soil maps and legacy soil data by serving as an eye-opener on the soil map to the wider community.

Development and Application of a Soil Moisture Downscaling Method for Mobility Assessment

DTIC Science & Technology

2011-05-01

instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send...REPORT Development and Application of a Soil Moisture Downscaling Method for Mobility Assessment 14. ABSTRACT 16. SECURITY CLASSIFICATION OF: Soil...cells). Thus, a method is required to downscale intermediate-resolution patterns to finer resolutions. Fortunately, fine-resolution variations in

A statistical approach for validating eSOTER and digital soil maps in front of traditional soil maps

NASA Astrophysics Data System (ADS)

Bock, Michael; Baritz, Rainer; Köthe, Rüdiger; Melms, Stephan; Günther, Susann

2015-04-01

During the European research project eSOTER, three different Digital Soil Maps (DSM) were developed for the pilot area Chemnitz 1:250,000 (FP7 eSOTER project, grant agreement nr. 211578). The core task of the project was to revise the SOTER method for the interpretation of soil and terrain data. It was one of the working hypothesis that eSOTER does not only provide terrain data with typical soil profiles, but that the new products actually perform like a conceptual soil map. The three eSOTER maps for the pilot area considerably differed in spatial representation and content of soil classes. In this study we compare the three eSOTER maps against existing reconnaissance soil maps keeping in mind that traditional soil maps have many subjective issues and intended bias regarding the overestimation and emphasize of certain features. Hence, a true validation of the proper representation of modeled soil maps is hardly possible; rather a statistical comparison between modeled and empirical approaches is possible. If eSOTER data represent conceptual soil maps, then different eSOTER, DSM and conventional maps from various sources and different regions could be harmonized towards consistent new data sets for large areas including the whole European continent. One of the eSOTER maps has been developed closely to the traditional SOTER method: terrain classification data (derived from SRTM DEM) were combined with lithology data (re-interpreted geological map); the corresponding terrain units were then extended with soil information: a very dense regional soil profile data set was used to define soil mapping units based on a statistical grouping of terrain units. The second map is a pure DSM map using continuous terrain parameters instead of terrain classification; radiospectrometric data were used to supplement parent material information from geology maps. The classification method Random Forest was used. The third approach predicts soil diagnostic properties based on covariates similar to DSM practices; in addition, multi-temporal MODIS data were used; the resulting soil map is the product of these diagnostic layers producing a map of soil reference groups (classified according to WRB). Because the third approach was applied to a larger test area in central Europe, and compared to the first two approaches, has worked with coarser input data, comparability is only partly fulfilled. To evaluate the usability of the three eSOTER maps, and to make a comparison among them, traditional soil maps 1:200,000 and 1:50,000 were used as reference data sets. Three statistical methods were applied: (i) in a moving window the distribution of the soil classes of each DSM product was compared to that of the soil maps by calculating the corrected coefficient of contingency, (ii) the value of predictive power for each of the eSOTER maps was determined, and (iii) the degree of consistency was derived. The latter is based on a weighting of the match of occurring class combinations via expert knowledge and recalculating the proportions of map appearance with these weights. To re-check the validation results a field study by local soil experts was conducted. The results show clearly that the first eSOTER approach based on the terrain classification / reinterpreted parent material information has the greatest similarity with traditional soil maps. The spatial differentiation offered by such an approach is well suitable to serve as a conceptual soil map. Therefore, eSOTER can be a tool for soil mappers to generate conceptual soil maps in a faster and more consistent way. This conclusion is at least valid for overview scales such as 1.250,000.

Predominant-period site classification for response spectra prediction equations in Italy

USGS Publications Warehouse

Di Alessandro, Carola; Bonilla, Luis Fabian; Boore, David M.; Rovelli, Antonio; Scotti, Oona

2012-01-01

We propose a site‐classification scheme based on the predominant period of the site, as determined from the average horizontal‐to‐vertical (H/V) spectral ratios of ground motion. Our scheme extends Zhao et al. (2006) classifications by adding two classes, the most important of which is defined by flat H/V ratios with amplitudes less than 2. The proposed classification is investigated by using 5%‐damped response spectra from Italian earthquake records. We select a dataset of 602 three‐component analog and digital recordings from 120 earthquakes recorded at 214 seismic stations within a hypocentral distance of 200 km. Selected events are in the moment‐magnitude range 4.0≤Mw≤6.8 and focal depths from a few kilometers to 46 km. We computed H/V ratios for these data and used them to classify each site into one of six classes. We then investigate the impact of this classification scheme on empirical ground‐motion prediction equations (GMPEs) by comparing its performance with that of the conventional rock/soil classification. Although the adopted approach results in only a small reduction of the overall standard deviation, the use of H/V spectral ratios in site classification does capture the signature of sites with flat frequency‐response, as well as deep and shallow‐soil profiles, characterized by long‐ and short‐period resonance, respectively; in addition, the classification scheme is relatively quick and inexpensive, which is an advantage over schemes based on measurements of shear‐wave velocity.

Combined Resistivity and Shear Wave Velocity Soil-type Estimation Beneath a Coastal Protection Levee.

NASA Astrophysics Data System (ADS)

Lorenzo, J. M.; Goff, D.; Hayashi, K.

2015-12-01

Unconsolidated Holocene deltaic sediments comprise levee foundation soils in New Orleans, USA. Whereas geotechnical tests at point locations are indispensable for evaluating soil stability, the highly variable sedimentary facies of the Mississippi delta create difficulties to predict soil conditions between test locations. Combined electrical resistivity and seismic shear wave studies, calibrated to geotechnical data, may provide an efficient methodology to predict soil types between geotechnical sites at shallow depths (0- 10 m). The London Avenue Canal levee flank of New Orleans, which failed in the aftermath of Hurricane Katrina, 2005, presents a suitable site in which to pioneer these geophysical relationships. Preliminary cross-plots show electrically resistive, high-shear-wave velocity areas interpreted as low-permeability, resistive silt. In brackish coastal environments, low-resistivity and low-shear-wave-velocity areas may indicate both saturated, unconsolidated sands and low-rigidity clays. Via a polynomial approximation, soil sub-types of sand, silt and clay can be estimated by a cross-plot of S-wave velocity and resistivity. We confirm that existent boring log data fit reasonably well with the polynomial approximation where 2/3 of soil samples fall within their respective bounds—this approach represents a new classification system that could be used for other mid-latitude, fine-grained deltas.

Classification of spatially unresolved objects

NASA Technical Reports Server (NTRS)

Nalepka, R. F.; Horwitz, H. M.; Hyde, P. D.; Morgenstern, J. P.

1972-01-01

A proportion estimation technique for classification of multispectral scanner images is reported that uses data point averaging to extract and compute estimated proportions for a single average data point to classify spatial unresolved areas. Example extraction calculations of spectral signatures for bare soil, weeds, alfalfa, and barley prove quite accurate.

SoilGrids250m: Global gridded soil information based on machine learning

PubMed Central

Mendes de Jesus, Jorge; Heuvelink, Gerard B. M.; Ruiperez Gonzalez, Maria; Kilibarda, Milan; Blagotić, Aleksandar; Shangguan, Wei; Wright, Marvin N.; Geng, Xiaoyuan; Bauer-Marschallinger, Bernhard; Guevara, Mario Antonio; Vargas, Rodrigo; MacMillan, Robert A.; Batjes, Niels H.; Leenaars, Johan G. B.; Ribeiro, Eloi; Wheeler, Ichsani; Mantel, Stephan; Kempen, Bas

2017-01-01

This paper describes the technical development and accuracy assessment of the most recent and improved version of the SoilGrids system at 250m resolution (June 2016 update). SoilGrids provides global predictions for standard numeric soil properties (organic carbon, bulk density, Cation Exchange Capacity (CEC), pH, soil texture fractions and coarse fragments) at seven standard depths (0, 5, 15, 30, 60, 100 and 200 cm), in addition to predictions of depth to bedrock and distribution of soil classes based on the World Reference Base (WRB) and USDA classification systems (ca. 280 raster layers in total). Predictions were based on ca. 150,000 soil profiles used for training and a stack of 158 remote sensing-based soil covariates (primarily derived from MODIS land products, SRTM DEM derivatives, climatic images and global landform and lithology maps), which were used to fit an ensemble of machine learning methods—random forest and gradient boosting and/or multinomial logistic regression—as implemented in the R packages ranger, xgboost, nnet and caret. The results of 10–fold cross-validation show that the ensemble models explain between 56% (coarse fragments) and 83% (pH) of variation with an overall average of 61%. Improvements in the relative accuracy considering the amount of variation explained, in comparison to the previous version of SoilGrids at 1 km spatial resolution, range from 60 to 230%. Improvements can be attributed to: (1) the use of machine learning instead of linear regression, (2) to considerable investments in preparing finer resolution covariate layers and (3) to insertion of additional soil profiles. Further development of SoilGrids could include refinement of methods to incorporate input uncertainties and derivation of posterior probability distributions (per pixel), and further automation of spatial modeling so that soil maps can be generated for potentially hundreds of soil variables. Another area of future research is the development of methods for multiscale merging of SoilGrids predictions with local and/or national gridded soil products (e.g. up to 50 m spatial resolution) so that increasingly more accurate, complete and consistent global soil information can be produced. SoilGrids are available under the Open Data Base License. PMID:28207752

SoilGrids250m: Global gridded soil information based on machine learning.

PubMed

Hengl, Tomislav; Mendes de Jesus, Jorge; Heuvelink, Gerard B M; Ruiperez Gonzalez, Maria; Kilibarda, Milan; Blagotić, Aleksandar; Shangguan, Wei; Wright, Marvin N; Geng, Xiaoyuan; Bauer-Marschallinger, Bernhard; Guevara, Mario Antonio; Vargas, Rodrigo; MacMillan, Robert A; Batjes, Niels H; Leenaars, Johan G B; Ribeiro, Eloi; Wheeler, Ichsani; Mantel, Stephan; Kempen, Bas

2017-01-01

This paper describes the technical development and accuracy assessment of the most recent and improved version of the SoilGrids system at 250m resolution (June 2016 update). SoilGrids provides global predictions for standard numeric soil properties (organic carbon, bulk density, Cation Exchange Capacity (CEC), pH, soil texture fractions and coarse fragments) at seven standard depths (0, 5, 15, 30, 60, 100 and 200 cm), in addition to predictions of depth to bedrock and distribution of soil classes based on the World Reference Base (WRB) and USDA classification systems (ca. 280 raster layers in total). Predictions were based on ca. 150,000 soil profiles used for training and a stack of 158 remote sensing-based soil covariates (primarily derived from MODIS land products, SRTM DEM derivatives, climatic images and global landform and lithology maps), which were used to fit an ensemble of machine learning methods-random forest and gradient boosting and/or multinomial logistic regression-as implemented in the R packages ranger, xgboost, nnet and caret. The results of 10-fold cross-validation show that the ensemble models explain between 56% (coarse fragments) and 83% (pH) of variation with an overall average of 61%. Improvements in the relative accuracy considering the amount of variation explained, in comparison to the previous version of SoilGrids at 1 km spatial resolution, range from 60 to 230%. Improvements can be attributed to: (1) the use of machine learning instead of linear regression, (2) to considerable investments in preparing finer resolution covariate layers and (3) to insertion of additional soil profiles. Further development of SoilGrids could include refinement of methods to incorporate input uncertainties and derivation of posterior probability distributions (per pixel), and further automation of spatial modeling so that soil maps can be generated for potentially hundreds of soil variables. Another area of future research is the development of methods for multiscale merging of SoilGrids predictions with local and/or national gridded soil products (e.g. up to 50 m spatial resolution) so that increasingly more accurate, complete and consistent global soil information can be produced. SoilGrids are available under the Open Data Base License.

A study of the utilization of ERTS-1 data from the Wabash River Basin

NASA Technical Reports Server (NTRS)

Landgrebe, D. A. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Nine projects are defined, five ERTS data applications experiments and four supporting technology tasks. The most significant applications results were achieved in the soil association mapping, earth surface feature identification, and urban land use mapping efforts. Four soil association boundaries were accurately delineated from ERTS-1 imagery. A data bank has been developed to test surface feature classifications obtained from ERTS-1 data. Preliminary forest cover classifications indicated that the number of acres estimated tended to be greater than actually existed by 25%. Urban land use analysis of ERTS-1 data indicated highly accurate classification could be obtained for many urban catagories. The wooded residential category tended to be misclassified as woods or agricultural land. Further statistical analysis revealed that these classes could be separated using sample variance.

Towards the development of multifunctional molecular indicators combining soil biogeochemical and microbiological variables to predict the ecological integrity of silvicultural practices.

PubMed

Peck, Vincent; Quiza, Liliana; Buffet, Jean-Philippe; Khdhiri, Mondher; Durand, Audrey-Anne; Paquette, Alain; Thiffault, Nelson; Messier, Christian; Beaulieu, Nadyre; Guertin, Claude; Constant, Philippe

2016-05-01

The impact of mechanical site preparation (MSP) on soil biogeochemical structure in young larch plantations was investigated. Soil samples were collected in replicated plots comprising simple trenching, double trenching, mounding and inverting site preparation. Unlogged natural mixed forest areas were used as a reference. Analysis of soil nutrients, abundance of bacteria and gas exchanges unveiled no significant difference among the plots. However, inverting site preparation resulted in higher variations of gas exchanges when compared with trenching, mounding and unlogged natural forest. A combination of the biological and physicochemical variables was used to define a multifunctional classification of the soil samples into four distinct groups categorized as a function of their deviation from baseline ecological conditions. According to this classification model, simple trenching was the approach that represented the lowest ecological risk potential at the microsite level. No relationship was observed between MSP method and soil bacterial community structure as assessed by high-throughput sequencing of bacterial 16S rRNA gene; however, indicator genotypes were identified for each multifunctional soil class. This is the first identification of multifunctional molecular indicators for baseline and disturbed ecological conditions in soil, demonstrating the potential of applied microbial ecology to guide silvicultural practices and ecological risk assessment. © 2016 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.

Soils and Vegetation of the Khaipudyr Bay Coast of the Barents Sea

NASA Astrophysics Data System (ADS)

Shamrikova, E. V.; Deneva, S. V.; Panyukov, A. N.; Kubik, O. S.

2018-04-01

Soils and vegetation of the coastal zone of the Khaipudyr Bay of the Barents Sea have been examined and compared with analogous objects in the Karelian coastal zone of the White Sea. The environmental conditions of these two areas are somewhat different: the climate of the Khaipudyr Bay coast is more severe, and the seawater salinity is higher (32-33‰ in the Khaipudyr Bay and 25-26‰ in the White Sea). The soil cover patterns of both regions are highly variable. Salt-affected marsh soils (Tidalic Fluvisols) are widespread. The complicated mesotopography includes high geomorphic positions that are not affected by tidal water. Under these conditions, zonal factors of pedogenesis predominate and lead to the development of Cryic Folic Histosols and Histic Reductaquic Cryosols. On low marshes, the concentrations of soluble Ca2+, K+ + Na+, Cl-, and SO2- 4 ions in the soils of the Khaipudyr Bay coast are two to four times higher than those in the analogous soils of Karelian coast. Cluster analysis of a number of soil characteristics allows separation of three soils groups: soils of low marshes, soils of middle-high marshes, and soils of higher positions developing under the impact of zonal factors together with the aerial transfer and deposition of seawater drops. The corresponding plant communities are represented by coastal sedge cenoses, forb-grassy halophytic cenoses, and zonal cenoses of hypoarctic tundra. It is argued that the grouping of marsh soils in the new substantivegenetic classification system of Russian soils requires further elaboration.

Geologic research in support of sustainable agriculture

USGS Publications Warehouse

Gough, L.P.; Herring, J.R.

1993-01-01

The importance and role of the geosciences in studies of sustainable agriculture include such traditional research areas as, agromineral resource assessments, the mapping and classification of soils and soil amendments, and the evaluation of landscapes for their vulnerability to physical and chemical degradation. Less traditional areas of study, that are increasing in societal importance because of environmental concerns and research into sustainable systems in general, include regional geochemical studies of plant and animal trace element deficiencies and toxicities, broad-scale water quality investigations, agricultural chemicals and the hydrogeologic interface, and minimally processed and ion-exchange agrominerals. We discuss the importance and future of phosphate in the US and world based on human population growth, projected agromineral demands in general, and the unavailability of new, high-quality agricultural lands. We also present examples of studies that relate geochemistry and the hydrogeologic characteristics of a region to the bioavailability and cycling of trace elements important to sustainable agricultural systems. ?? 1993.

Mapping Soil Carbon in the Yukon Kuskokwim River Delta Alaska

NASA Astrophysics Data System (ADS)

Natali, S.; Fiske, G.; Schade, J. D.; Mann, P. J.; Holmes, R. M.; Ludwig, S.; Melton, S.; Sae-lim, N.; Jardine, L. E.; Navarro-Perez, E.

2017-12-01

Arctic river deltas are hotspots for carbon storage, occupying <1% of the pan-Arctic watershed but containing >10% of carbon stored in arctic permafrost. The Yukon Kuskokwim (YK) Delta, Alaska is located in the lower latitudinal range of the northern permafrost region in an area of relatively warm permafrost that is particularly vulnerable to warming climate. Active layer depths range from 50 cm on peat plateaus to >100 cm in wetland and aquatic ecosystems. The size of the soil organic carbon pool and vulnerability of the carbon in the YK Delta is a major unknown and is critically important as climate warming and increasing fire frequency may make this carbon vulnerable to transport to aquatic and marine systems and the atmosphere. To characterize the size and distribution of soil carbon pools in the YK Delta, we mapped the land cover of a 1910 km2 watershed located in a region of the YK Delta that was impacted by fire in 2015. The map product was the result of an unsupervised classification using the Weka K Means clustering algorithm implemented in Google's Earth Engine. Inputs to the classification were Worldview2 resolution optical imagery (1m), Arctic DEM (5m), and Sentinel 2 level 1C multispectral imagery, including NDVI, (10 m). We collected 100 soil cores (0-30 cm) from sites of different land cover and landscape position, including moist and dry peat plateaus, high and low intensity burned plateaus, fens, and drained lakes; 13 lake sediment cores (0-50 cm); and 20 surface permafrost cores (to 100 cm) from burned and unburned peat plateaus. Active layer and permafrost soils were analyzed for organic matter content, soil moisture content, and carbon and nitrogen pools (30 and 100 cm). Soil carbon content varied across the landscape; average carbon content values for lake sediments were 12% (5- 17% range), fens 26% (9-44%), unburned peat plateaus 41% (34-44%), burned peat plateaus 19% (7-34%). These values will be used to estimate soil carbon pools, which will be applied to the spatial extent of each landcover class in our map, yielding a watershed-wide and spatially explicit map of soil carbon in the YK Delta. This map will provide the basis for understanding where carbon is stored in the watershed and the vulnerability of that carbon to climate change and fire.

Rapid Erosion Modeling in a Western Kenya Watershed using Visible Near Infrared Reflectance, Classification Tree Analysis and 137Cesium.

PubMed

deGraffenried, Jeff B; Shepherd, Keith D

2009-12-15

Human induced soil erosion has severe economic and environmental impacts throughout the world. It is more severe in the tropics than elsewhere and results in diminished food production and security. Kenya has limited arable land and 30 percent of the country experiences severe to very severe human induced soil degradation. The purpose of this research was to test visible near infrared diffuse reflectance spectroscopy (VNIR) as a tool for rapid assessment and benchmarking of soil condition and erosion severity class. The study was conducted in the Saiwa River watershed in the northern Rift Valley Province of western Kenya, a tropical highland area. Soil 137 Cs concentration was measured to validate spectrally derived erosion classes and establish the background levels for difference land use types. Results indicate VNIR could be used to accurately evaluate a large and diverse soil data set and predict soil erosion characteristics. Soil condition was spectrally assessed and modeled. Analysis of mean raw spectra indicated significant reflectance differences between soil erosion classes. The largest differences occurred between 1,350 and 1,950 nm with the largest separation occurring at 1,920 nm. Classification and Regression Tree (CART) analysis indicated that the spectral model had practical predictive success (72%) with Receiver Operating Characteristic (ROC) of 0.74. The change in 137 Cs concentrations supported the premise that VNIR is an effective tool for rapid screening of soil erosion condition.

Variation in soil macro-fauna diversity in seven humus orders of a Parrotio-Carpinetum forest association on Chromic Cambisols of Shast-klateh area in Iran

NASA Astrophysics Data System (ADS)

Izadi, M.; Habashi, H.; Waez-Mousavi, S. M.

2017-03-01

Soil biodiversity includes organisms which spend a part or all of their life cycle on or in the soil. Among soil-dwelling animals, macro-fauna as an important group of animals have important effects on the dynamics of soil organic matter and litter decomposition process. The humus forms interact with the climatic conditions, flora, as well as soil fauna, and microbial activity. In new humus form classifications, soil organisms play an important role in separation of humus horizons from one another. The subject of this study was to determine the diversity of macro fauna for different humus forms. We determined humus forms using morphological classification, and then 69 random samples were taken from plots of 100 cm2 in area, and soil macro-fauna species were collected by hand sorting method. Two classes of humus forms, including Mull (with three humus orders, namely Dysmull, Oligomull, and Mesomull,) and Amphi (with four humus orders, namely Leptoamphi, Eumacroamphi, Eumesoamphi, and Pachyamphi) were identified. A number of 13 macro-fauna orders were identified using identification key. Among the humus orders, Shannon diversity, Simpson evenness and Margalef richness indices were the highest in Pachyamphi order. Arthropod diversity in Pachyamphi humus order was higher than those of Mull. These results showed that diversity of soil macrofauna increase by increasing the thickness of the organic horizons (OL, OF, OH), especially OH horizon.

Assessment of Cropping System Diversity in the Fergana Valley Through Image Fusion of Landsat 8 and SENTINEL-1

NASA Astrophysics Data System (ADS)

Dimov, D.; Kuhn, J.; Conrad, C.

2016-06-01

In the transitioning agricultural societies of the world, food security is an essential element of livelihood and economic development with the agricultural sector very often being the major employment factor and income source. Rapid population growth, urbanization, pollution, desertification, soil degradation and climate change pose a variety of threats to a sustainable agricultural development and can be expressed as agricultural vulnerability components. Diverse cropping patterns may help to adapt the agricultural systems to those hazards in terms of increasing the potential yield and resilience to water scarcity. Thus, the quantification of crop diversity using indices like the Simpson Index of Diversity (SID) e.g. through freely available remote sensing data becomes a very important issue. This however requires accurate land use classifications. In this study, the focus is set on the cropping system diversity of garden plots, summer crop fields and orchard plots which are the prevalent agricultural systems in the test area of the Fergana Valley in Uzbekistan. In order to improve the accuracy of land use classification algorithms with low or medium resolution data, a novel processing chain through the hitherto unique fusion of optical and SAR data from the Landsat 8 and Sentinel-1 platforms is proposed. The combination of both sensors is intended to enhance the object's textural and spectral signature rather than just to enhance the spatial context through pansharpening. It could be concluded that the Ehlers fusion algorithm gave the most suitable results. Based on the derived image fusion different object-based image classification algorithms such as SVM, Naïve Bayesian and Random Forest were evaluated whereby the latter one achieved the highest classification accuracy. Subsequently, the SID was applied to measure the diversification of the three main cropping systems.

Classification of permafrost active layer depth from remotely sensed and topographic evidence

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peddle, D.R.; Franklin, S.E.

1993-04-01

The remote detection of permafrost (perennially frozen ground) has important implications to environmental resource development, engineering studies, natural hazard prediction, and climate change research. In this study, the authors present results from two experiments into the classification of permafrost active layer depth within the zone of discontinuous permafrost in northern Canada. A new software system based on evidential reasoning was implemented to permit the integrated classification of multisource data consisting of landcover, terrain aspect, and equivalent latitude, each of which possessed different formats, data types, or statistical properties that could not be handled by conventional classification algorithms available to thismore » study. In the first experiment, four active layer depth classes were classified using ground based measurements of the three variables with an accuracy of 83% compared to in situ soil probe determination of permafrost active layer depth at over 500 field sites. This confirmed the environmental significance of the variables selected, and provided a baseline result to which a remote sensing classification could be compared. In the second experiment, evidence for each input variable was obtained from image processing of digital SPOT imagery and a photogrammetric digital elevation model, and used to classify active layer depth with an accuracy of 79%. These results suggest the classification of evidence from remotely sensed measures of spectral response and topography may provide suitable indicators of permafrost active layer depth.« less

The Low Backscattering Objects Classification in Polsar Image Based on Bag of Words Model Using Support Vector Machine

NASA Astrophysics Data System (ADS)

Yang, L.; Shi, L.; Li, P.; Yang, J.; Zhao, L.; Zhao, B.

2018-04-01

Due to the forward scattering and block of radar signal, the water, bare soil, shadow, named low backscattering objects (LBOs), often present low backscattering intensity in polarimetric synthetic aperture radar (PolSAR) image. Because the LBOs rise similar backscattering intensity and polarimetric responses, the spectral-based classifiers are inefficient to deal with LBO classification, such as Wishart method. Although some polarimetric features had been exploited to relieve the confusion phenomenon, the backscattering features are still found unstable when the system noise floor varies in the range direction. This paper will introduce a simple but effective scene classification method based on Bag of Words (BoW) model using Support Vector Machine (SVM) to discriminate the LBOs, without relying on any polarimetric features. In the proposed approach, square windows are firstly opened around the LBOs adaptively to determine the scene images, and then the Scale-Invariant Feature Transform (SIFT) points are detected in training and test scenes. The several SIFT features detected are clustered using K-means to obtain certain cluster centers as the visual word lists and scene images are represented using word frequency. At last, the SVM is selected for training and predicting new scenes as some kind of LBOs. The proposed method is executed over two AIRSAR data sets at C band and L band, including water, bare soil and shadow scenes. The experimental results illustrate the effectiveness of the scene method in distinguishing LBOs.

A Geostatistical Toolset for Reconstructing Louisiana's Coastal Stratigraphy using Subsurface Boring and Cone Penetrometer Test Data

NASA Astrophysics Data System (ADS)

Li, A.; Tsai, F. T. C.; Jafari, N.; Chen, Q. J.; Bentley, S. J.

2017-12-01

A vast area of river deltaic wetlands stretches across southern Louisiana coast. The wetlands are suffering from a high rate of land loss, which increasingly threats coastal community and energy infrastructure. A regional stratigraphic framework of the delta plain is now imperative to answer scientific questions (such as how the delta plain grows and decays?) and to provide information to coastal protection and restoration projects (such as marsh creation and construction of levees and floodwalls). Through years, subsurface investigations in Louisiana have been conducted by state and federal agencies (Louisiana Department of Natural Resources, United States Geological Survey, United States Army Corps of Engineers, etc.), research institutes (Louisiana Geological Survey, LSU Coastal Studies Institute, etc.), engineering firms, and oil-gas companies. This has resulted in the availability of various types of data, including geological, geotechnical, and geophysical data. However, it is challenging to integrate different types of data and construct three-dimensional stratigraphy models in regional scale. In this study, a set of geostatistical methods were used to tackle this problem. An ordinary kriging method was used to regionalize continuous data, such as grain size, water content, liquid limit, plasticity index, and cone penetrometer tests (CPTs). Indicator kriging and multiple indicator kriging methods were used to regionalize categorized data, such as soil classification. A compositional kriging method was used to regionalize compositional data, such as soil composition (fractions of sand, silt and clay). Stratigraphy models were constructed for three cases in the coastal zone: (1) Inner Harbor Navigation Canal (IHNC) area: soil classification and soil behavior type (SBT) stratigraphies were constructed using ordinary kriging; (2) Middle Barataria Bay area: a soil classification stratigraphy was constructed using multiple indicator kriging; (3) Lower Barataria Bay and Lower Breton Sound areas: a soil texture stratigraphy was constructed using soil compositional data and compositional kriging. Cross sections were extracted from the three-dimensional stratigraphy models to reveal spatial distributions of different stratigraphic features.

A model for predicting embankment slope failures in clay-rich soils; A Louisiana example

NASA Astrophysics Data System (ADS)

Burns, S. F.

2015-12-01

A model for predicting embankment slope failures in clay-rich soils; A Louisiana example It is well known that smectite-rich soils significantly reduce the stability of slopes. The question is how much smectite in the soil causes slope failures. A study of over 100 sites in north and south Louisiana, USA, compared slopes that failed during a major El Nino winter (heavy rainfall) in 1982-1983 to similar slopes that did not fail. Soils in the slopes were tested for per cent clay, liquid limits, plasticity indices and semi-quantitative clay mineralogy. Slopes with the High Risk for failure (85-90% chance of failure in 8-15 years after construction) contained soils with a liquid limit > 54%, a plasticity index over 29%, and clay contents > 47%. Slopes with an Intermediate Risk (55-50% chance of failure in 8-15 years) contained soils with a liquid limit between 36-54%, plasticity index between 16-19%, and clay content between 32-47%. Slopes with a Low Risk chance of failure (< 5% chance of failure in 8-15 years after construction) contained soils with a liquid limit < 36%, a plasticity index < 16%, and a clay content < 32%. These data show that if one is constructing embankments and one wants to prevent slope failure of the 3:1 slopes, check the above soil characteristics before construction. If the soils fall into the Low Risk classification, construct the embankment normally. If the soils fall into the High Risk classification, one will need to use lime stabilization or heat treatments to prevent failures. Soils in the Intermediate Risk class will have to be evaluated on a case by case basis.

Sequence of Changes in Maize Responding to Soil Water Deficit and Related Critical Thresholds

PubMed Central

Ma, Xueyan; He, Qijin; Zhou, Guangsheng

2018-01-01

The sequence of changes in crop responding to soil water deficit and related critical thresholds are essential for better drought damage classification and drought monitoring indicators. This study was aimed to investigate the critical thresholds of maize growth and physiological characteristics responding to changing soil water and to reveal the sequence of changes in maize responding to soil water deficit both in seedling and jointing stages based on 2-year’s maize field experiment responding to six initial soil water statuses conducted in 2013 and 2014. Normal distribution tolerance limits were newly adopted to identify critical thresholds of maize growth and physiological characteristics to a wide range of soil water status. The results showed that in both stages maize growth characteristics related to plant water status [stem moisture content (SMC) and leaf moisture content (LMC)], leaf gas exchange [net photosynthetic rate (Pn), transpiration rate (Tr), and stomatal conductance (Gs)], and leaf area were sensitive to soil water deficit, while biomass-related characteristics were less sensitive. Under the concurrent weather conditions and agronomic managements, the critical soil water thresholds in terms of relative soil moisture of 0–30 cm depth (RSM) of maize SMC, LMC, net Pn, Tr, Gs, and leaf area were 72, 65, 62, 60, 58, and 46%, respectively, in seedling stage, and 64, 64, 51, 53, 48, and 46%, respectively, in jointing stage. It indicated that there is a sequence of changes in maize responding to soil water deficit, i.e., their response sequences as soil water deficit intensified: SMC ≥ LMC > leaf gas exchange > leaf area in both stages. This sequence of changes in maize responding to soil water deficit and related critical thresholds may be better indicators of damage classification and drought monitoring. PMID:29765381

Impact of improved soil climatology and intialization on WRF-chem dust simulations over West Asia

NASA Astrophysics Data System (ADS)

Omid Nabavi, Seyed; Haimberger, Leopold; Samimi, Cyrus

2016-04-01

Meteorological forecast models such as WRF-chem are designed to forecast not only standard atmospheric parameters but also aerosol, particularly mineral dust concentrations. It has therefore become an important tool for the prediction of dust storms in West Asia where dust storms have the considerable impact on living conditions. However, verification of forecasts against satellite data indicates only moderate skill in prediction of such events. Earlier studies have already indicated that the erosion factor, land use classification, soil moisture, and temperature initializations play a critical role in the accuracy of WRF-chem dust simulations. In the standard setting the erosion factor and land use classification are based on topographic variations and post-processed images of the advanced very high-resolution radiometer (AVHRR) during the period April 1992-March 1993. Furthermore, WRF-chem is normally initialized by the soil moisture and temperature of Final Analysis (FNL) model on 1.0x1.0 degree grids. In this study, we have changed boundary initial conditions so that they better represent current changing environmental conditions. To do so, land use (only bare soil class) and the erosion factor were both modified using information from MODIS deep blue AOD (Aerosol Optical Depth). In this method, bare soils are where the relative frequency of dust occurrence (deep blue AOD > 0.5) is more than one-third of a given month. Subsequently, the erosion factor, limited within the bare soil class, is determined by the monthly frequency of dust occurrence ranging from 0.3 to 1. It is worth to mention, that 50 percent of calculated erosion factor is afterward assigned to sand class while silt and clay classes each gain 25 percent of it. Soil moisture and temperature from the Global Land Data Assimilation System (GLDAS) were utilized to provide these initializations in higher resolution of 0.25 degree than in the standard setting. Modified and control simulations were conducted for the summertime of 2008-2012 and verified by satellite data (MODIS deep blue AOD, TOMs Aerosol Index and MISR AOD 550nm) and two well-known modeling systems of atmospheric composition (MACC and DREAM). All comparisons show a significant improvement in WRF-chem dust simulations after implementing the modifications. In comparison to the control run, the modified run bears an average increase of spearman correlation of 17-20 percent points when it is compared with satellite data. Our runs with modified WRF-chem even outperform MACC and DREAM dust simulations for the region.

Hydrological Climate Classification: Can We Improve on Köppen-Geiger?

NASA Astrophysics Data System (ADS)

Knoben, W.; Woods, R. A.; Freer, J. E.

2017-12-01

Classification is essential in the study of complex natural systems, yet hydrology so far has no formal way to structure the climate forcing which underlies hydrologic response. Various climate classification systems can be borrowed from other disciplines but these are based on different organizing principles than a hydrological classification might use. From gridded global data we calculate a gridded aridity index, an aridity seasonality index and a rain-vs-snow index, which we use to cluster global locations into climate groups. We then define the membership degree of nearly 1100 catchments to each of our climate groups based on each catchment's climate and investigate the extent to which streamflow responses within each climate group are similar. We compare this climate classification approach with the often-used Köppen-Geiger classification, using statistical tests based on streamflow signature values. We find that three climate indices are sufficient to distinguish 18 different climate types world-wide. Climates tend to change gradually in space and catchments can thus belong to multiple climate groups, albeit with different degrees of membership. Streamflow responses within a climate group tend to be similar, regardless of the catchments' geographical proximity. A Wilcoxon two-sample test based on streamflow signature values for each climate group shows that the new classification can distinguish different flow regimes using this classification scheme. The Köppen-Geiger approach uses 29 climate classes but is less able to differentiate streamflow regimes. Climate forcing exerts a strong control on typical hydrologic response and both change gradually in space. This makes arbitrary hard boundaries in any classification scheme difficult to defend. Any hydrological classification should thus acknowledge these gradual changes in forcing. Catchment characteristics (soil or vegetation type, land use, etc) can vary more quickly in space than climate does, which can explain streamflow differences between geographically close locations. Summarizing, this work shows that hydrology needs its own way to structure climate forcing, acknowledging that climates vary gradually on a global scale and explicitly including those climate aspects that drive seasonal changes in hydrologic regimes.

Nondestructive Evaluation of Airport Pavements. Volume I. Program References,

DTIC Science & Technology

1979-09-01

greater than its original capacity (see test 13 on Fig. 2.5). During the material tests by Majidzadeh, the dynamic E-value of frozen subgrade soil was...Sample the base and subbase material by conventional spoon and identify the material by standard soil -aggregate classification and penetration...such as shaker table. The new testing specification is designed for all paving materials including subgrade soils . The specifications of material

Predicting fire severity using surface fuels and moisture

Treesearch

Pamela G. Sikkink; Robert E. Keane

2012-01-01

Fire severity classifications have been used extensively in fire management over the last 30 years to describe specific environmental or ecological impacts of fire on fuels, vegetation, wildlife, and soils in recently burned areas. New fire severity classifications need to be more objective, predictive, and ultimately more useful to fire management and planning. Our...

Traditional knowledge among Zapotecs of Sierra Madre Del Sur, Oaxaca. Does it represent a base for plant resources management and conservation?

PubMed Central

2012-01-01

Traditional classification systems represent cognitive processes of human cultures in the world. It synthesizes specific conceptions of nature, as well as cumulative learning, beliefs and customs that are part of a particular human community or society. Traditional knowledge has been analyzed from different viewpoints, one of which corresponds to the analysis of ethnoclassifications. In this work, a brief analysis of the botanical traditional knowledge among Zapotecs of the municipality of San Agustin Loxicha, Oaxaca was conducted. The purposes of this study were: a) to analyze the traditional ecological knowledge of local plant resources through the folk classification of both landscapes and plants and b) to determine the role that this knowledge has played in plant resource management and conservation. The study was developed in five communities of San Agustín Loxicha. From field trips, plant specimens were collected and showed to local people in order to get the Spanish or Zapotec names; through interviews with local people, we obtained names and identified classification categories of plants, vegetation units, and soil types. We found a logic structure in Zapotec plant names, based on linguistic terms, as well as morphological and ecological caracteristics. We followed the classification principles proposed by Berlin [6] in order to build a hierarchical structure of life forms, names and other characteristics mentioned by people. We recorded 757 plant names. Most of them (67%) have an equivalent Zapotec name and the remaining 33% had mixed names with Zapotec and Spanish terms. Plants were categorized as native plants, plants introduced in pre-Hispanic times, or plants introduced later. All of them are grouped in a hierarchical classification, which include life form, generic, specific, and varietal categories. Monotypic and polytypic names are used to further classify plants. This holistic classification system plays an important role for local people in many aspects: it helps to organize and make sense of the diversity, to understand the interrelation among plants–soil–vegetation and to classify their physical space since they relate plants with a particular vegetation unit and a kind of soil. The locals also make a rational use of these elements, because they know which crops can grow in any vegetation unit, or which places are indicated to recollect plants. These aspects are interconnected and could be fundamental for a rational use and management of plant resources. PMID:22789155

Influence of Fines Content on Consolidation and Compressibility Characteristics of Granular Materials

NASA Astrophysics Data System (ADS)

Lipiński, Mirosław J.; Wdowska, Małgorzata K.; Jaroń, Łukasz

2017-10-01

Various behaviour of soil under loading results to large extent from kind of soil considered. There is a lot of literature concerning pure sand or plastic clays, while little is known about materials, which are from classification point of view, between those soils. These materials can be considered as cohesionless soils with various fines content. The paper present results of tests carried out in large consolidometer on three kinds of soil, containing 10, 36 and 97% of fines content. Consolidation, permeability and compressibility characteristics were determined. Analysis of the test results allowed to formulate conclusion concerning change in soil behaviour resulting from fines content.

Rangeland degradation in savannas of South Africa: spatial patterns of soil and vegetation

NASA Astrophysics Data System (ADS)

Sandhage-Hofmann, Alexandra; Löffler, Jörg; du Preez, Chris; Kotzé, Elmarie; Weijers, Stef; Wundram, Dirk; Zacharias, Maximilan; Amelung, Wulf

2017-04-01

Extensive bush encroachment by Acacia mellifera and associated woody species at semi-arid and arid sites are the most notable forms of rangeland degradation in savannas of South Africa. Concerns are growing over the threat of suppression and loss of nutritious perennial grass species. Grazing and different rangeland management systems (communal and freehold) are considered to be of major importance for degradation, but the process of encroachment is not restricted to communal land. A vegetation change is mostly accompanied by changes in soil properties, where soils in savanna systems can profit from woody species due to litter fall, root distribution, shadow and animal resting time. Savannas are very heterogeneous systems with high spatial variation of patches with wood, herbaceous species and bare ground. We hypothesized that the spatial patterns of soil properties in South Africás rangelands are controlled by present or past vegetation, modulated by the tenure systems with higher rangeland degradation in communal areas. To test this, we sampled soils at communal and commercial land in the Kuruman area of South Africa with the following design: three farms per tenure system, 6 randomly chosen plots (100x100m) per farm, and 25 soil samples (0-10 cm) per plot, each in a 5x5m sampling area. At every sampling point, information of overlying vegetation was recorded (species or bare soil, canopy size, height). For each sampling area, if present, trees/ shrubs were sampled and their ages estimated through the counting of annual growth rings. For each plot, high resolution UAV aerial photos were taken to evaluate the extent of bush encroachment. Analyses involved main physical and chemical soil parameters and isotopic analyses. The results of a rough aerial image classification (grass, woody species, bare ground) revealed significant differences between the tenure systems with higher coverage of bare ground and shrubs at communal farms, and higher grass cover at commercial farms. The tenure systems had no differences in main texture classes of the soils, but significant differences in the composition of the sand fraction, with higher levels of fine sand and lower levels of coarse sand in communal farms. The chemical soil properties showed a high variability both within and between the farms, with much higher variability within communal than commercial farms. Additionally, concentrations of nitrogen, carbon, calcium and pH were significant higher in communal farms. Isotopic analyses in soils showed significant differences for 15N with higher levels in commercial farms. Different photosynthetic pathways are responsible for differences found in 13C values, with higher levels (-16-18‰) in C4-grassland and lower values (-22-26‰) in soils under Acacia (C3). We found relationships between soil properties and species or bare ground, where differences in texture likely interact with both, vegetation cover and soil properties.

GIS/RS-based Rapid Reassessment for Slope Land Capability Classification

NASA Astrophysics Data System (ADS)

Chang, T. Y.; Chompuchan, C.

2014-12-01

Farmland resources in Taiwan are limited because about 73% is mountainous and slope land. Moreover, the rapid urbanization and dense population resulted in the highly developed flat area. Therefore, the utilization of slope land for agriculture is more needed. In 1976, "Slope Land Conservation and Utilization Act" was promulgated to regulate the slope land utilization. Consequently, slope land capability was categorized into Class I-IV according to 4 criteria, i.e., average land slope, effective soil depth, degree of soil erosion, and parent rock. The slope land capability Class I-VI are suitable for cultivation and pasture. Whereas, Class V should be used for forestry purpose and Class VI should be the conservation land which requires intensive conservation practices. The field survey was conducted to categorize each land unit as the classification scheme. The landowners may not allow to overuse land capability limitation. In the last decade, typhoons and landslides frequently devastated in Taiwan. The rapid post-disaster reassessment of the slope land capability classification is necessary. However, the large-scale disaster on slope land is the constraint of field investigation. This study focused on using satellite remote sensing and GIS as the rapid re-evaluation method. Chenyulan watershed in Nantou County, Taiwan was selected to be a case study area. Grid-based slope derivation, topographic wetness index (TWI) and USLE soil loss calculation were used to classify slope land capability. The results showed that GIS-based classification give an overall accuracy of 68.32%. In addition, the post-disaster areas of Typhoon Morakot in 2009, which interpreted by SPOT satellite imageries, were suggested to classify as the conservation lands. These tools perform better in the large coverage post-disaster update for slope land capability classification and reduce time-consuming, manpower and material resources to the field investigation.

Tools based on multivariate statistical analysis for classification of soil and groundwater in Apulian agricultural sites.

PubMed

Ielpo, Pierina; Leardi, Riccardo; Pappagallo, Giuseppe; Uricchio, Vito Felice

2017-06-01

In this paper, the results obtained from multivariate statistical techniques such as PCA (Principal component analysis) and LDA (Linear discriminant analysis) applied to a wide soil data set are presented. The results have been compared with those obtained on a groundwater data set, whose samples were collected together with soil ones, within the project "Improvement of the Regional Agro-meteorological Monitoring Network (2004-2007)". LDA, applied to soil data, has allowed to distinguish the geographical origin of the sample from either one of the two macroaeras: Bari and Foggia provinces vs Brindisi, Lecce e Taranto provinces, with a percentage of correct prediction in cross validation of 87%. In the case of the groundwater data set, the best classification was obtained when the samples were grouped into three macroareas: Foggia province, Bari province and Brindisi, Lecce and Taranto provinces, by reaching a percentage of correct predictions in cross validation of 84%. The obtained information can be very useful in supporting soil and water resource management, such as the reduction of water consumption and the reduction of energy and chemical (nutrients and pesticides) inputs in agriculture.

Hyperspectral detection of a subsurface CO2 leak in the presence of water stressed vegetation.

PubMed

Bellante, Gabriel J; Powell, Scott L; Lawrence, Rick L; Repasky, Kevin S; Dougher, Tracy

2014-01-01

Remote sensing of vegetation stress has been posed as a possible large area monitoring tool for surface CO2 leakage from geologic carbon sequestration (GCS) sites since vegetation is adversely affected by elevated CO2 levels in soil. However, the extent to which remote sensing could be used for CO2 leak detection depends on the spectral separability of the plant stress signal caused by various factors, including elevated soil CO2 and water stress. This distinction is crucial to determining the seasonality and appropriateness of remote GCS site monitoring. A greenhouse experiment tested the degree to which plants stressed by elevated soil CO2 could be distinguished from plants that were water stressed. A randomized block design assigned Alfalfa plants (Medicago sativa) to one of four possible treatment groups: 1) a CO2 injection group; 2) a water stress group; 3) an interaction group that was subjected to both water stress and CO2 injection; or 4) a group that received adequate water and no CO2 injection. Single date classification trees were developed to identify individual spectral bands that were significant in distinguishing between CO2 and water stress agents, in addition to a random forest classifier that was used to further understand and validate predictive accuracies. Overall peak classification accuracy was 90% (Kappa of 0.87) for the classification tree analysis and 83% (Kappa of 0.77) for the random forest classifier, demonstrating that vegetation stressed from an underground CO2 leak could be accurately discerned from healthy vegetation and areas of co-occurring water stressed vegetation at certain times. Plants appear to hit a stress threshold, however, that would render detection of a CO2 leak unlikely during severe drought conditions. Our findings suggest that early detection of a CO2 leak with an aerial or ground-based hyperspectral imaging system is possible and could be an important GCS monitoring tool.

Hyperspectral Detection of a Subsurface CO2 Leak in the Presence of Water Stressed Vegetation

PubMed Central

Bellante, Gabriel J.; Powell, Scott L.; Lawrence, Rick L.; Repasky, Kevin S.; Dougher, Tracy

2014-01-01

Remote sensing of vegetation stress has been posed as a possible large area monitoring tool for surface CO2 leakage from geologic carbon sequestration (GCS) sites since vegetation is adversely affected by elevated CO2 levels in soil. However, the extent to which remote sensing could be used for CO2 leak detection depends on the spectral separability of the plant stress signal caused by various factors, including elevated soil CO2 and water stress. This distinction is crucial to determining the seasonality and appropriateness of remote GCS site monitoring. A greenhouse experiment tested the degree to which plants stressed by elevated soil CO2 could be distinguished from plants that were water stressed. A randomized block design assigned Alfalfa plants (Medicago sativa) to one of four possible treatment groups: 1) a CO2 injection group; 2) a water stress group; 3) an interaction group that was subjected to both water stress and CO2 injection; or 4) a group that received adequate water and no CO2 injection. Single date classification trees were developed to identify individual spectral bands that were significant in distinguishing between CO2 and water stress agents, in addition to a random forest classifier that was used to further understand and validate predictive accuracies. Overall peak classification accuracy was 90% (Kappa of 0.87) for the classification tree analysis and 83% (Kappa of 0.77) for the random forest classifier, demonstrating that vegetation stressed from an underground CO2 leak could be accurately discerned from healthy vegetation and areas of co-occurring water stressed vegetation at certain times. Plants appear to hit a stress threshold, however, that would render detection of a CO2 leak unlikely during severe drought conditions. Our findings suggest that early detection of a CO2 leak with an aerial or ground-based hyperspectral imaging system is possible and could be an important GCS monitoring tool. PMID:25330232

The creation of digital thematic soil maps at the regional level (with the map of soil carbon pools in the Usa River basin as an example)

NASA Astrophysics Data System (ADS)

Pastukhov, A. V.; Kaverin, D. A.; Shchanov, V. M.

2016-09-01

A digital map of soil carbon pools was created for the forest-tundra ecotone in the Usa River basin with the use of ERDAS Imagine 2014 and ArcGIS 10.2 software. Supervised classification and thematic interpretation of satellite images and digital terrain models with the use of a georeferenced database on soil profiles were applied. Expert assessment of the natural diversity and representativeness of random samples for different soil groups was performed, and the minimal necessary size of the statistical sample was determined.

Identification and classification of structural soil conservation measures based on very high resolution stereo satellite data.

PubMed

Eckert, Sandra; Tesfay Ghebremicael, Selamawit; Hurni, Hans; Kohler, Thomas

2017-05-15

Land degradation affects large areas of land around the globe, with grave consequences for those living off the land. Major efforts are being made to implement soil and water conservation measures that counteract soil erosion and help secure vital ecosystem services. However, where and to what extent such measures have been implemented is often not well documented. Knowledge about this could help to identify areas where soil and water conservation measures are successfully supporting sustainable land management, as well as areas requiring urgent rehabilitation of conservation structures such as terraces and bunds. This study explores the potential of the latest satellite-based remote sensing technology for use in assessing and monitoring the extent of existing soil and water conservation structures. We used a set of very high resolution stereo Geoeye-1 satellite data, from which we derived a detailed digital surface model as well as a set of other spectral, terrain, texture, and filtered information layers. We developed and applied an object-based classification approach, working on two segmentation levels. On the coarser level, the aim was to delimit certain landscape zones. Information about these landscape zones is useful in distinguishing different types of soil and water conservation structures, as each zone contains certain specific types of structures. On the finer level, the goal was to extract and identify different types of linear soil and water conservation structures. The classification rules were based mainly on spectral, textural, shape, and topographic properties, and included object relationships. This approach enabled us to identify and separate from other classes the majority (78.5%) of terraces and bunds, as well as most hillside terraces (81.25%). Omission and commission errors are similar to those obtained by the few existing studies focusing on the same research objective but using different types of remotely sensed data. Based on our results, we estimate that the construction of the conservation structures in our study area in Eritrea required over 300,000 person-days of work, which underlines the huge efforts involved in soil and water conservation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Extending a field-based Sonoran desert vegetation classification to a regional scale using optical and microwave satellite imagery

NASA Astrophysics Data System (ADS)

Shupe, Scott Marshall

2000-10-01

Vegetation mapping in and regions facilitates ecological studies, land management, and provides a record to which future land changes can be compared. Accurate and representative mapping of desert vegetation requires a sound field sampling program and a methodology to transform the data collected into a representative classification system. Time and cost constraints require that a remote sensing approach be used if such a classification system is to be applied on a regional scale. However, desert vegetation may be sparse and thus difficult to sense at typical satellite resolutions, especially given the problem of soil reflectance. This study was designed to address these concerns by conducting vegetation mapping research using field and satellite data from the US Army Yuma Proving Ground (USYPG) in Southwest Arizona. Line and belt transect data from the Army's Land Condition Trend Analysis (LCTA) Program were transformed into relative cover and relative density classification schemes using cluster analysis. Ordination analysis of the same data produced two and three-dimensional graphs on which the homogeneity of each vegetation class could be examined. It was found that the use of correspondence analysis (CA), detrended correspondence analysis (DCA), and non-metric multidimensional scaling (NMS) ordination methods was superior to the use of any single ordination method for helping to clarify between-class and within-class relationships in vegetation composition. Analysis of these between-class and within-class relationships were of key importance in examining how well relative cover and relative density schemes characterize the USYPG vegetation. Using these two classification schemes as reference data, maximum likelihood and artificial neural net classifications were then performed on a coregistered dataset consisting of a summer Landsat Thematic Mapper (TM) image, one spring and one summer ERS-1 microwave image, and elevation, slope, and aspect layers. Classifications using a combination of ERS-1 imagery and elevation, slope, and aspect data were superior to classifications carried out using Landsat TM data alone. In all classification iterations it was consistently found that the highest classification accuracy was obtained by using a combination of Landsat TM, ERS-1, and elevation, slope, and aspect data. Maximum likelihood classification accuracy was found to be higher than artificial neural net classification in all cases.

Development of a national geodatabase (Greece) for soil surveys and land evaluation using space technology and GIS

NASA Astrophysics Data System (ADS)

Bilas, George; Dionysiou, Nina; Karapetsas, Nikolaos; Silleos, Nikolaos; Kosmas, Konstantinos; Misopollinos, Nikolaos

2016-04-01

This project was funded by OPEKEPE, Ministry of Agricultural Development and Food, Greece and involves development of a national geodatabase and a WebGIS that encompass soil data of all the agricultural areas of Greece in order to supply the country with a multi-purpose master plan for agricultural land management. The area mapped covered more than 385,000 ha divided in more than 9.000 Soil Mapping Units (SMUs) based on physiographic analysis, field work and photo interpretation of satellite images. The field work included description and sampling in three depths (0-30, 30-60 and >60 cm) of 2,000 soil profiles and 8,000 augers (sampling 0-30 and >30 cm). In total more than 22,000 soil samples were collected and analyzed for determining main soil properties associated with soil classification and soil evaluation. Additionally the project included (1) integration of all data in the Soil Geodatabase, (2) finalization of SMUs, (3) development of a Master Plan for Agricultural Land Management and (4) development and operational testing of the Web Portal for e-information and e-services. The integrated system is expected, after being fully operational, to provide important electronic services and benefits to farmers, private sector and governmental organizations. An e-book with the soil maps of Greece was also provided including 570 sheets with data description and legends. The Master Plan for Agricultural Land Management includes soil quality maps for 30 agricultural crops, together with maps showing soil degradation risks, such as erosion, desertification, salinity and nitrates, thus providing the tools for soil conservation and sustainable land management.

Classification of hydrogeologic areas and hydrogeologic flow systems in the basin and range physiographic province, southwestern United States

USGS Publications Warehouse

Anning, David W.; Konieczki, Alice D.

2005-01-01

The hydrogeology of the Basin and Range Physiographic Province in parts of Arizona, California, New Mexico, Utah, and most of Nevada was classified at basin and larger scales to facilitate information transfer and to provide a synthesis of results from many previous hydrologic investigations. A conceptual model for the spatial hierarchy of the hydrogeology was developed for the Basin and Range Physiographic Province and consists, in order of increasing spatial scale, of hydrogeologic components, hydrogeologic areas, hydrogeologic flow systems, and hydrogeologic regions. This hierarchy formed a framework for hydrogeologic classification. Hydrogeologic areas consist of coincident ground-water and surface-water basins and were delineated on the basis of existing sets of basin boundaries that were used in past investigations by State and Federal government agencies. Within the study area, 344 hydrogeologic areas were identified and delineated. This set of basins not only provides a framework for the classification developed in this report, but also has value for regional and subregional purposes of inventory, study, analysis, and planning throughout the Basin and Range Physiographic Province. The fact that nearly all of the province is delineated by the hydrogeologic areas makes this set well suited to support regional-scale investigations. Hydrogeologic areas are conceptualized as a control volume consisting of three hydrogeologic components: the soils and streams, basin fill, and consolidated rocks. The soils and streams hydrogeologic component consists of all surface-water bodies and soils extending to the bottom of the plant root zone. The basin-fill hydrogeologic component consists of unconsolidated and semiconsolidated sediment deposited in the structural basin. The consolidated-rocks hydrogeologic component consists of the crystalline and sedimentary rocks that form the mountain blocks and basement rock of the structural basin. Hydrogeologic areas were classified into 19 groups through a cluster analysis of 8 characteristics of each area's hydrologic system. Six characteristics represented the inflows and outflows of water through the soils and streams, basin fill, and consolidated rocks, and can be used to determine the hydrogeologic area's position in a hydrogeologic flow system. Source-, link-, and sink-type hydrogeologic areas have outflow but not inflow, inflow and outflow, and inflow but not outflow, respectively, through one or more of the three hydrogeologic components. Isolated hydrogeologic areas have no inflow or outflow through any of the three hydrogeologic components. The remaining two characteristics are indexes that represent natural recharge and discharge processes and anthropogenic recharge and discharge processes occurring in the hydrogeologic area. Of the 19 groups of hydrogeologic areas, 1 consisted of predominantly isolated-type hydrogeologic areas, 7 consisted of source-type hydrogeologic areas, 9 consisted of link-type hydrogeologic areas, and 2 consisted of sink-type hydrogeologic areas. Groups comprising the source-, link-, and sink-type hydrogeologic areas can be distinguished between each other on the basis of the hydrogeologic component(s) through which interbasin flow occurs, as well as typical values for the two indexes. Conceptual models of the hydrologic systems of a representative hydrogeologic area for each group were developed to help distinguish groups and to synthesize the variation in hydrogeologic systems in the Basin and Range Physiographic Province. Hydrogeologic flow systems consist of either a single isolated hydrogeologic area or a series of multiple hydrogeologic areas that are hydraulically connected through interbasin flows. A total of 54 hydrogeologic flow systems were identified and classified into 9 groups. One group consisted of single isolated hydrogeologic areas. The remaining eight groups consisted of multiple hydrogeologic areas and were distinguished o

Goal oriented soil mapping: applying modern methods supported by local knowledge: A review

NASA Astrophysics Data System (ADS)

Pereira, Paulo; Brevik, Eric; Oliva, Marc; Estebaranz, Ferran; Depellegrin, Daniel; Novara, Agata; Cerda, Artemi; Menshov, Oleksandr

2017-04-01

In the recent years the amount of soil data available increased importantly. This facilitated the production of better and accurate maps, important for sustainable land management (Pereira et al., 2017). Despite these advances, the human knowledge is extremely important to understand the natural characteristics of the landscape. The knowledge accumulated and transmitted generation after generation is priceless, and should be considered as a valuable data source for soil mapping and modelling. The local knowledge and wisdom can complement the new advances in soil analysis. In addition, farmers are the most interested in the participation and incorporation of their knowledge in the models, since they are the end-users of the study that soil scientists produce. Integration of local community's vision and understanding about nature is assumed to be an important step to the implementation of decision maker's policies. Despite this, many challenges appear regarding the integration of local and scientific knowledge, since in some cases there is no spatial correlation between folk and scientific classifications, which may be attributed to the different cultural variables that influence local soil classification. The objective of this work is to review how modern soil methods incorporated local knowledge in their models. References Pereira, P., Brevik, E., Oliva, M., Estebaranz, F., Depellegrin, D., Novara, A., Cerda, A., Menshov, O. (2017) Goal Oriented soil mapping: applying modern methods supported by local knowledge. In: Pereira, P., Brevik, E., Munoz-Rojas, M., Miller, B. (Eds.) Soil mapping and process modelling for sustainable land use management (Elsevier Publishing House) ISBN: 9780128052006

Soil and Land Resources Information System (SLISYS-Tarim) for Sustainable Management of River Oases along the Tarim River, China

NASA Astrophysics Data System (ADS)

Othmanli, Hussein; Zhao, Chengyi; Stahr, Karl

2017-04-01

The Tarim River Basin is the largest continental basin in China. The region has extremely continental desert climate characterized by little rainfall <50 mm/a and high potential evaporation >3000 mm/a. The climate change is affecting severely the basin causing soil salinization, water shortage, and regression in crop production. Therefore, a Soil and Land Resources Information System (SLISYS-Tarim) for the regional simulation of crop yield production in the basin was developed. The SLISYS-Tarim consists of a database and an agro-ecological simulation model EPIC (Environmental Policy Integrated Climate). The database comprises relational tables including information about soils, terrain conditions, land use, and climate. The soil data implicate information of 50 soil profiles which were dug, analyzed, described and classified in order to characterize the soils in the region. DEM data were integrated with geological maps to build a digital terrain structure. Remote sensing data of Landsat images were applied for soil mapping, and for land use and land cover classification. An additional database for climate data, land management and crop information were linked to the system, too. Construction of the SLISYS-Tarim database was accomplished by integrating and overlaying the recommended thematic maps within environment of the geographic information system (GIS) to meet the data standard of the global and national SOTER digital database. This database forms appropriate input- and output data for the crop modelling with the EPIC model at various scales in the Tarim Basin. The EPIC model was run for simulating cotton production under a constructed scenario characterizing the current management practices, soil properties and climate conditions. For the EPIC model calibration, some parameters were adjusted so that the modeled cotton yield fits to the measured yield on the filed scale. The validation of the modeling results was achieved in a later step based on remote sensing data. The simulated cotton yield varied according to field management, soil type and salinity level, where soil salinity was the main limiting factor. Furthermore, the calibrated and validated EPIC model was run under several scenarios of climate conditions and land management practices to estimate the effect of climate change on cotton production and sustainability of agriculture systems in the basin. The application of SLISYS-Tarim showed that this database can be a suitable framework for storage and retrieval of soil and terrain data at various scales. The simulation with the EPIC model can assess the impact of climate change and management strategies. Therefore, SLISYS-Tarim can be a good tool for regional planning and serve the decision support system on regional and national scale.

Centrifugal Modelling of Soil Structures. Part I. Centrifugal Modelling of Slope Failures.

DTIC Science & Technology

1979-03-01

comparing successive photographs in which soil movement was noted by the change in position of the original grid of silvered indicator balls . Inherent in...SECIJ RITY CLASSIFICATION OF THIS PAGE(1Thon Pat& Entered) of uplift forces was also observed. In nineteen coal mine waste embankment dam models...In’nineteen coal mine waste embankment dam models, throughout which the soil particle size distribution was altered for modelling of dif- ferent

Development of SMAP Mission Cal/Val Activities

NASA Technical Reports Server (NTRS)

Colliander, A.; Jackson, T.; Kimball, J.; Cosh, M.; Spencer, M.; Entekhabi, D.; Njoku, E.; ONeill, P.

2010-01-01

The Soil Moisture Active Passive (SMAP) mission is a NASA directed mission to map global land surface soil moisture and freeze-thaw state. Instrument and mission details are shown. The key SMAP soil moisture product is provided at 10 km resolution with 0.04cubic cm/cubic cm accuracy. The freeze/thaw product is provided at 3 km resolution and 80% frozen-thawed classification accuracy. The full list of SMAP data products is shown.

Ecotoxicological characterization of hazardous wastes.

PubMed

Wilke, B-M; Riepert, F; Koch, Christine; Kühne, T

2008-06-01

In Europe hazardous wastes are classified by 14 criteria including ecotoxicity (H 14). Standardized methods originally developed for chemical and soil testing were adapted for the ecotoxicological characterization of wastes including leachate and solid phase tests. A consensus on which tests should be recommended as mandatory is still missing. Up to now, only a guidance on how to proceed with the preparation of waste materials has been standardized by CEN as EN 14735. In this study, tests including higher plants, earthworms, collembolans, microorganisms, duckweed and luminescent bacteria were selected to characterize the ecotoxicological potential of a boiler slag, a dried sewage sludge, a thin sludge and a waste petrol. In general, the instructions given in EN 14735 were suitable for all wastes used. The evaluation of the different test systems by determining the LC/EC(50) or NOEC-values revealed that the collembolan reproduction and the duckweed frond numbers were the most sensitive endpoints. For a final classification and ranking of wastes the Toxicity Classification System (TCS) using EC/LC(50) values seems to be appropriate.

Distinct growth strategies of soil bacteria as revealed by large-scale colony tracking.

PubMed

Ernebjerg, Morten; Kishony, Roy

2012-03-01

Our understanding of microbial ecology has been significantly furthered in recent years by advances in sequencing techniques, but comprehensive surveys of the phenotypic characteristics of environmental bacteria remain rare. Such phenotypic data are crucial for understanding the microbial strategies for growth and the diversity of microbial ecosystems. Here, we describe a high-throughput measurement of the growth of thousands of bacterial colonies using an array of flat-bed scanners coupled with automated image analysis. We used this system to investigate the growth properties of members of a microbial community from untreated soil. The system provides high-quality measurements of the number of CFU, colony growth rates, and appearance times, allowing us to directly study the distribution of these properties in mixed environmental samples. We find that soil bacteria display a wide range of growth strategies which can be grouped into several clusters that cannot be reduced to any of the classical dichotomous divisions of soil bacteria, e.g., into copiotophs and oligotrophs. We also find that, at early times, cells are most likely to form colonies when other, nearby colonies are present but not too dense. This maximization of culturability at intermediate plating densities suggests that the previously observed tendency for high density to lead to fewer colonies is partly offset by the induction of colony formation caused by interactions between microbes. These results suggest new types of growth classification of soil bacteria and potential effects of species interactions on colony growth.

Soil Quality Indicator: a new concept

NASA Astrophysics Data System (ADS)

Barão, Lúcia; Basch, Gottlieb

2017-04-01

During the last century, cultivated soils have been intensively exploited for food and feed production. This exploitation has compromised the soils' natural functions and many of the soil-mediated ecosystems services, including its production potential for agriculture. Also, soils became increasingly vulnerable and less resilient to a wide range of threats. To overcome this situation, new and better management practices are needed to prevent soil from degradation. However, to adopt the best management practices in a specific location, it is necessary to evaluate the soil quality status first. Different soil quality indicators have been suggested over the last decades in order to evaluate the soil status, and those are often based on the performance of soil chemical, physical and biological properties. However, the direct link between these properties and the associated soil functions or soil vulnerability to threats appears more difficult to be established. This present work is part of the iSQAPER project- Interactive Soil Quality Assessment in Europe and China for Agricultural Productivity and Environmental Resilience, where new soil quality concepts are explored to provide better information regarding the effects of the most promising agricultural management practices on soil quality. We have developed a new conceptual soil quality indicator which determines the soil quality status, regarding its vulnerability towards different threats. First, different indicators were specifically developed for each of the eight threats considered - Erosion, SOM decline, Poor Structure, Poor water holding capacity, Compaction, N-Leaching, Soil-borne pests and diseases and Salinization. As an example for the case of Erosion, the RUSLE equation for the estimate of the soil annual loss was used. Secondly, a reference classification was established for each indicator to integrate all possible results into a Good, Intermediate or Bad classification. Finally, all indicators were combined to return a single evaluation of the soil status, using different techniques that are dependent on the final use of the soil quality indicator. Some of the advantages of this new concept include the evaluation of soil quality based on its vulnerability to threats, together with the evaluation of soil properties in a given context while also suggesting soil management practices that are directly capable to mitigate soil vulnerability towards specific threats. Keywords: Soil Quality, Agriculture, Sustainability, Soil threats

Raster Vs. Point Cloud LiDAR Data Classification

NASA Astrophysics Data System (ADS)

El-Ashmawy, N.; Shaker, A.

2014-09-01

Airborne Laser Scanning systems with light detection and ranging (LiDAR) technology is one of the fast and accurate 3D point data acquisition techniques. Generating accurate digital terrain and/or surface models (DTM/DSM) is the main application of collecting LiDAR range data. Recently, LiDAR range and intensity data have been used for land cover classification applications. Data range and Intensity, (strength of the backscattered signals measured by the LiDAR systems), are affected by the flying height, the ground elevation, scanning angle and the physical characteristics of the objects surface. These effects may lead to uneven distribution of point cloud or some gaps that may affect the classification process. Researchers have investigated the conversion of LiDAR range point data to raster image for terrain modelling. Interpolation techniques have been used to achieve the best representation of surfaces, and to fill the gaps between the LiDAR footprints. Interpolation methods are also investigated to generate LiDAR range and intensity image data for land cover classification applications. In this paper, different approach has been followed to classifying the LiDAR data (range and intensity) for land cover mapping. The methodology relies on the classification of the point cloud data based on their range and intensity and then converted the classified points into raster image. The gaps in the data are filled based on the classes of the nearest neighbour. Land cover maps are produced using two approaches using: (a) the conventional raster image data based on point interpolation; and (b) the proposed point data classification. A study area covering an urban district in Burnaby, British Colombia, Canada, is selected to compare the results of the two approaches. Five different land cover classes can be distinguished in that area: buildings, roads and parking areas, trees, low vegetation (grass), and bare soil. The results show that an improvement of around 10 % in the classification results can be achieved by using the proposed approach.

Field validation of Burned Area Reflectance Classification (BARC) products for post fire assessment

Treesearch

Andrew T. Hudak; Peter R. Robichaud; Jeffery B. Evans; Jess Clark; Keith Lannom; Penelope Morgan; Carter Stone

2004-01-01

The USFS Remote Sensing Applications Center (RSAC) and the USGS EROS Data Center (EDC) produce Burned Area Reflectance Classification (BARC) maps for use by Burned Area Emergency Rehabilitation (BAER) teams in rapid response to wildfires. BAER teams desire maps indicative of soil burn severity, but photosynthetic and nonphotosynthetic vegetation also influences the...

The comparative evaluation of ERTS-1 imagery for resource inventory in land use planning. [Oregon - Newberry Caldera, Mt. Washington, and Big Summit Prairie in Crook County

NASA Technical Reports Server (NTRS)

Schrumpf, B. J. (Principal Investigator); Simonson, G. H.; Paine, D. P.; Lawrence, R. D.; Pyott, W. T.; Herzog, J. H.; Murray, R. J.; Norgren, J. A.; Cornwell, J. A.; Rogers, R. A.

1974-01-01

The author has identified the following significant results. Multidiscipline team interpretation and mapping of resources for Crook County is complete on 1:250,000 scale enlargements of ERTS imagery and 1:120,000 hi-flight photography. Maps of geology, soils, vegetation-land use and land resources units were interpreted to show limitations, suitabilities, and geologic hazards for land use planning. Mapping of lineaments and structures from ERTS imagery has shown a number of features not previously mapped in Oregon. A multistage timber inventory of Ochoco National Forest was made, using ERTS images as the first stage. Inventory of forest clear-cutting practices was successfully demonstrated with color composites. Soil tonal differences in fallow fields correspond with major soil boundaries in loess-mantled terrain. A digital classification system used for discriminating natural vegetation and geologic material classes was successful in separating most major classes around Newberry Caldera, Mt. Washington, and Big Summit Prairie.

Testing the Potential of Vegetation Indices for Land Use/cover Classification Using High Resolution Data

NASA Astrophysics Data System (ADS)

Karakacan Kuzucu, A.; Bektas Balcik, F.

2017-11-01

Accurate and reliable land use/land cover (LULC) information obtained by remote sensing technology is necessary in many applications such as environmental monitoring, agricultural management, urban planning, hydrological applications, soil management, vegetation condition study and suitability analysis. But this information still remains a challenge especially in heterogeneous landscapes covering urban and rural areas due to spectrally similar LULC features. In parallel with technological developments, supplementary data such as satellite-derived spectral indices have begun to be used as additional bands in classification to produce data with high accuracy. The aim of this research is to test the potential of spectral vegetation indices combination with supervised classification methods and to extract reliable LULC information from SPOT 7 multispectral imagery. The Normalized Difference Vegetation Index (NDVI), the Ratio Vegetation Index (RATIO), the Soil Adjusted Vegetation Index (SAVI) were the three vegetation indices used in this study. The classical maximum likelihood classifier (MLC) and support vector machine (SVM) algorithm were applied to classify SPOT 7 image. Catalca is selected region located in the north west of the Istanbul in Turkey, which has complex landscape covering artificial surface, forest and natural area, agricultural field, quarry/mining area, pasture/scrubland and water body. Accuracy assessment of all classified images was performed through overall accuracy and kappa coefficient. The results indicated that the incorporation of these three different vegetation indices decrease the classification accuracy for the MLC and SVM classification. In addition, the maximum likelihood classification slightly outperformed the support vector machine classification approach in both overall accuracy and kappa statistics.

Soil-geographical and ecological tour in West-Russia: 20 years anniversary

NASA Astrophysics Data System (ADS)

Kuzyakov, Yakov

2013-04-01

Soil-geographical and agro-ecological tour in Russia celebrated in this summer its 20 years anniversary! More than 800 students, PhD students and researcher from Germany, Switzerland, Austria, Sweden and France participated at the tour since 1993. The majority of the participants were students studying soil science, geoecology, geography, agriculture and ecology. The tour is based on a classical Russian zonal approach: a cross-section of climatic zones starting from south taiga, through deciduous forest, forest steppe, steppe, dry steppe, to semi dessert and transition to the desert zone. In each zone the specifics of climate, vegetation, nutrient cycling, and of course soil genesis as well as soil use by forestry and agriculture are described. Half of the soil group units of WRB classification (2006) are presented on about 35 soil profile pits and are described with focus on pedogenic processes and soil forming factors. The following soil groups are described in details by horizons according to WRB soil classification (2006): Arenosols, Podzols, Albeluvisols Histosols, Gleysols, Luvisols, Phaeozems, Chernozems, Kastanozems, Calcisols, Vertisols, Leptosols, Fluvisols, Solonetzes, Solonchaks. In addition to natural conditions, large-scale experiments designing agricultural landscapes (stone steppe), biosphere reserves and conservation areas (Tula-Schneisen, Divnogor'je, Baskunchak), as well as collective agricultural farms (previously kolkhoz) are visited to evaluate the anthropogenic effects on ecosystems and especially on soils. The 2.5 weeks bus journey through many villages and small towns, visits of museums and historical monuments, introduction in the settlement development of different regions provide a broad presentation of Russian history, traditions, life style, and contemporary state. So, combination of very diverse educational part focused on soil and environmental conditions with anthropogenic impacts and local history as well as recent socioeconomic developments make the tour unique and very attractive for BSc and MSc students and soil science professionals. Detailed information about the next tour is under: www.uni-goettingen.de/soilrus

The effects of vegetation and soil hydraulic properties on passive microwave sensing of soil moisture: Data report for the 1982 fiels experiments

NASA Technical Reports Server (NTRS)

Oneill, P.; Jackson, T.; Blanchard, B. J.; Vandenhoek, R.; Gould, W.; Wang, J.; Glazar, W.; Mcmurtrey, J., III

1983-01-01

Field experiments to (1) study the biomass and geometrical structure properties of vegetation canopies to determine their impact on microwave emission data, and (2) to verify whether time series microwave data can be related to soil hydrologic properties for use in soil type classification. Truck mounted radiometers at 1.4 GHz and 5 GHz were used to obtain microwave brightness temperatures of bare vegetated test plots under different conditions of soil wetness, plant water content and canopy structure. Observations of soil moisture, soil temperature, vegetation biomass and other soil and canopy parameters were made concurrently with the microwave measurements. The experimental design and data collection procedures for both experiments are documented and the reduced data are presented in tabular form.

The nature and classification of Australian soils affected by sodium

NASA Astrophysics Data System (ADS)

Murphy, Brian; Greene, Richard; Harms, Ben

2017-04-01

Large areas of Australia are affected by the processes of salinity and sodicity and they are important processes to understand as they can result in the degradation of agricultural lands used for both intensive cropping and extensive grazing practices. Sodic soils are defined as those having ESP of at least 6% in Australia. Northcote and Skene (1972) estimated that of Australia's total area of 770 M ha, 39 M ha was affected by salinity and 193-257 M ha by sodicity. However, in a more recent publication, Rengasamy (2006), quoted the areas of saline and sodic soils as 66 M ha and 340 M ha respectively. The soils affected by sodium in Australia include a large group of contrasting soils (Northcote and Skene 1972). Based on the Australian soil classification, included are: • Alkaline strongly sodic to sodic clay soils with uniform texture profiles - largely Vertosols 666 400 km2 • Alkaline strongly sodic to sodic coarse and medium textured soils with uniform and gradational texture profiles - largely Calcarosols 600 700 km2 • Alkaline strongly sodic to sodic texture contrast soils - largely Sodosols 454 400 km2 • Non-alkaline sodic and strongly sodic neutral texture contrast soils - largely Sodosols 134 700 km2 • Non-alkaline sodic acid texture contrast soils - Sodosols and Kurosols 140 700 km2 Many Australian sodic soils have not developed by the traditional solonetz process of leaching of a solonchak, but rather have developed by the accumulation of sodium on the cation exchange complex in preference to the other exchangeable cations without any recognisable intermediate saline phase occurring. This is especially the case for the sodic, non-alkaline texture contrast soils or Sodosols. The major sodic soil group in WRB is the Solonetz soils. These require the presence of a Natric horizon which has to contain illuviated clay and at least 15% ESP. However, there is provision for Sodic qualifiers with at least 6% ESP for many other reference Soil Groups including the Vertisols, Luvisols, Calcisols and Planosols which would have some relationship to Australia's sodic soils.

Assessment of Sampling Approaches for Remote Sensing Image Classification in the Iranian Playa Margins

NASA Astrophysics Data System (ADS)

Kazem Alavipanah, Seyed

There are some problems in soil salinity studies based upon remotely sensed data: 1-spectral world is full of ambiguity and therefore soil reflectance can not be attributed to a single soil property such as salinity, 2) soil surface conditions as a function of time and space is a complex phenomena, 3) vegetation with a dynamic biological nature may create some problems in the study of soil salinity. Due to these problems the first question which may arise is how to overcome or minimise these problems. In this study we hypothesised that different sources of data, well established sampling plan and optimum approach could be useful. In order to choose representative training sites in the Iranian playa margins, to define the spectral and informational classes and to overcome some problems encountered in the variation within the field, the following attempts were made: 1) Principal Component Analysis (PCA) in order: a) to determine the most important variables, b) to understand the Landsat satellite images and the most informative components, 2) the photomorphic unit (PMU) consideration and interpretation; 3) study of salt accumulation and salt distribution in the soil profile, 4) use of several forms of field data, such as geologic, geomorphologic and soil information; 6) confirmation of field data and land cover types with farmers and the members of the team. The results led us to find at suitable approaches with a high and acceptable image classification accuracy and image interpretation. KEY WORDS; Photo Morphic Unit, Pprincipal Ccomponent Analysis, Soil Salinity, Field Work, Remote Sensing

Evaluation of Electromagnetic Induction to Characterize and Map Sodium-Affected Soils in the Northern Great Plains of the United States

NASA Astrophysics Data System (ADS)

Brevik, E. C.; Heilig, J.; Kempenich, J.; Doolittle, J.; Ulmer, M.

2012-04-01

Sodium-affected soils (SAS) cover over 4 million hectares in the Northern Great Plains of the United States. Improving the classification, interpretation, and mapping of SAS is a major goal of the United States Department of Agriculture-Natural Resource Conservation Service (USDA-NRCS) as Northern Great Plains soil surveys are updated. Apparent electrical conductivity (ECa) as measured with ground conductivity meters has shown promise for mapping SAS, however, this use of this geophysical tool needs additional evaluation. This study used an EM-38 MK2-2 meter (Geonics Limited, Mississauga, Ontario), a Trimble AgGPS 114 L-band DGPS (Trimble, Sunnyvale, CA) and the RTmap38MK2 program (Geomar Software, Inc., Mississauga, Ontario) on an Allegro CX field computer (Juniper Systems, North Logan, UT) to collect, observe, and interpret ECa data in the field. The ECa map generated on-site was then used to guide collection of soil samples for soil characterization and to evaluate the influence of soil properties in SAS on ECa as measured with the EM-38MK2-2. Stochastic models contained in the ESAP software package were used to estimate the SAR and salinity levels from the measured ECa data in 30 cm depth intervals to a depth of 90 cm and for the bulk soil (0 to 90 cm). This technique showed promise, with meaningful spatial patterns apparent in the ECa data. However, many of the stochastic models used for salinity and SAR for individual depth intervals and for the bulk soil had low R-squared values. At both sites, significant variability in soil clay and water contents along with a small number of soil samples taken to calibrate the ECa values to soil properties likely contributed to these low R-squared values.

Vertisols and vertic soils of the middle and lower Volga regions

NASA Astrophysics Data System (ADS)

Khitrov, N. B.; Rogovneva, L. V.

2014-12-01

In addition to the earlier known vertic alluvial soils (slitozems) of the Volga-Akhtuba floodplain, 44 new areas of Vertisols and vertic soils (according to the WRB), or dark slitozems (according to the new Russian soil classification system), have been found in the Middle and Lower Volga regions from the forest-steppe to the semidesert zones. Though these soils occupy relatively small areas, they are regularly found in the studied regions. Vertisols developed from the clayey alluvial sediments occur in widened parts of the central floodplain in the areas of strong meandering of the river downstream from the areas, where it washes out ancient swelling clay sediments. Many areas of Vertisols and vertic soils are confined to the second Khvalyn terrace of the Volga River composed of the chocolate-brown swelling Khvalyn clay. These soils do not occupy the entire terrace. They have an insular-type distribution and highly diverse in their properties. In the soils developed from the eluvium of the microlayered chocolate-brown marine clay within the Privolzhskaya Upland, vertic features are absent. The destruction of the lithogenic layering in the course of the redeposition of the marine clay with the formation of the new Quaternary clayey sediments creates conditions for the development of vertic soils. The northernmost area of Vertisols proper has been found in the area of the Samara Arc (53.231° N, 049.322° E). The soils with vertic features have been found in Mordovia and Samara oblast even further to the north (up to 54.2° N). Morphometric data on the slickensides, wedge-shaped structure, and depth of the soil cracking are presented.

The Northern Circumpolar Soil Carbon Database: spatially distributed datasets of soil coverage and soil carbon storage in the northern permafrost regions

NASA Astrophysics Data System (ADS)

Hugelius, G.; Tarnocai, C.; Broll, G.; Canadell, J. G.; Kuhry, P.; Swanson, D. K.

2012-08-01

High latitude terrestrial ecosystems are key components in the global carbon (C) cycle. Estimates of global soil organic carbon (SOC), however, do not include updated estimates of SOC storage in permafrost-affected soils or representation of the unique pedogenic processes that affect these soils. The Northern Circumpolar Soil Carbon Database (NCSCD) was developed to quantify the SOC stocks in the circumpolar permafrost region (18.7 × 106 km2). The NCSCD is a polygon-based digital database compiled from harmonized regional soil classification maps in which data on soil order coverage has been linked to pedon data (n = 1647) from the northern permafrost regions to calculate SOC content and mass. In addition, new gridded datasets at different spatial resolutions have been generated to facilitate research applications using the NCSCD (standard raster formats for use in Geographic Information Systems and Network Common Data Form files common for applications in numerical models). This paper describes the compilation of the NCSCD spatial framework, the soil sampling and soil analyses procedures used to derive SOC content in pedons from North America and Eurasia and the formatting of the digital files that are available online. The potential applications and limitations of the NCSCD in spatial analyses are also discussed. The database has the doi:10.5879/ecds/00000001. An open access data-portal with all the described GIS-datasets is available online at: http://dev1.geo.su.se/bbcc/dev/ncscd/.

The Northern Circumpolar Soil Carbon Database: spatially distributed datasets of soil coverage and soil carbon storage in the northern permafrost regions

NASA Astrophysics Data System (ADS)

Hugelius, G.; Tarnocai, C.; Broll, G.; Canadell, J. G.; Kuhry, P.; Swanson, D. K.

2013-01-01

High-latitude terrestrial ecosystems are key components in the global carbon (C) cycle. Estimates of global soil organic carbon (SOC), however, do not include updated estimates of SOC storage in permafrost-affected soils or representation of the unique pedogenic processes that affect these soils. The Northern Circumpolar Soil Carbon Database (NCSCD) was developed to quantify the SOC stocks in the circumpolar permafrost region (18.7 × 106 km2). The NCSCD is a polygon-based digital database compiled from harmonized regional soil classification maps in which data on soil order coverage have been linked to pedon data (n = 1778) from the northern permafrost regions to calculate SOC content and mass. In addition, new gridded datasets at different spatial resolutions have been generated to facilitate research applications using the NCSCD (standard raster formats for use in geographic information systems and Network Common Data Form files common for applications in numerical models). This paper describes the compilation of the NCSCD spatial framework, the soil sampling and soil analytical procedures used to derive SOC content in pedons from North America and Eurasia and the formatting of the digital files that are available online. The potential applications and limitations of the NCSCD in spatial analyses are also discussed. The database has the doi:10.5879/ecds/00000001. An open access data portal with all the described GIS-datasets is available online at: http://www.bbcc.su.se/data/ncscd/.

Indices of soil contamination by heavy metals - methodology of calculation for pollution assessment (minireview).

PubMed

Weissmannová, Helena Doležalová; Pavlovský, Jiří

2017-11-07

This article provides the assessment of heavy metal soil pollution with using the calculation of various pollution indices and contains also summarization of the sources of heavy metal soil pollution. Twenty described indices of the assessment of soil pollution consist of two groups: single indices and total complex indices of pollution or contamination with relevant classes of pollution. This minireview provides also the classification of pollution indices in terms of the complex assessment of soil quality. In addition, based on the comparison of metal concentrations in soil-selected sites of the world and used indices of pollution or contamination in soils, the concentration of heavy metal in contaminated soils varied widely, and pollution indices confirmed the significant contribution of soil pollution from anthropogenic activities mainly in urban and industrial areas.

Spatial disaggregation of complex soil map units at regional scale based on soil-landscape relationships

NASA Astrophysics Data System (ADS)

Vincent, Sébastien; Lemercier, Blandine; Berthier, Lionel; Walter, Christian

2015-04-01

Accurate soil information over large extent is essential to manage agronomical and environmental issues. Where it exists, information on soil is often sparse or available at coarser resolution than required. Typically, the spatial distribution of soil at regional scale is represented as a set of polygons defining soil map units (SMU), each one describing several soil types not spatially delineated, and a semantic database describing these objects. Delineation of soil types within SMU, ie spatial disaggregation of SMU allows improved soil information's accuracy using legacy data. The aim of this study was to predict soil types by spatial disaggregation of SMU through a decision tree approach, considering expert knowledge on soil-landscape relationships embedded in soil databases. The DSMART (Disaggregation and Harmonization of Soil Map Units Through resampled Classification Trees) algorithm developed by Odgers et al. (2014) was used. It requires soil information, environmental covariates, and calibration samples, to build then extrapolate decision trees. To assign a soil type to a particular spatial position, a weighed random allocation approach is applied: each soil type in the SMU is weighted according to its assumed proportion of occurrence in the SMU. Thus soil-landscape relationships are not considered in the current version of DSMART. Expert rules on soil distribution considering the relief, parent material and wetlands location were proposed to drive the procedure of allocation of soil type to sampled positions, in order to integrate the soil-landscape relationships. Semantic information about spatial organization of soil types within SMU and exhaustive landscape descriptors were used. In the eastern part of Brittany (NW France), 171 soil types were described; their relative area in the SMU were estimated, geomorphological and geological contexts were recorded. The model predicted 144 soil types. An external validation was performed by comparing predicted with effectively observed soil types derived from available soil maps at scale of 1:25.000 or 1:50.000. Overall accuracies were 63.1% and 36.2%, respectively considering or not the adjacent pixels. The introduction of expert rules based on soil-landscape relationships to allocate soil types to calibration samples enhanced dramatically the results in comparison with a simple weighted random allocation procedure. It also enabled the production of a comprehensive soil map, retrieving expected spatial organization of soils. Estimation of soil properties for various depths is planned using disaggregated soil types, according to the GlobalSoilmap.net specifications. Odgers, N.P., Sun, W., McBratney, A.B., Minasny, B., Clifford, D., 2014. Disaggregating and harmonising soil map units through resampled classification trees. Geoderma 214, 91-100.

A preliminary riparian/wetland vegetation community classification of the Upper and Middle Rio Grande watersheds in New Mexico

Treesearch

Paula Durkin; Esteban Muldavin; Mike Bradley; Stacey E. Carr

1996-01-01

The riparian wetland vegetation communities of the upper and middle Rio Grande watersheds in New Mexico were surveyed in 1992 through 1994. The communities are hierarchically classified in terms of species composition and vegetation structure. The resulting Community Types are related to soil conditions, hydrological regime, and temporal dynamics. The classification is...

Lesson Plans for Teaching Basic Vocational Agriculture. Section III. Introduction to Soil Management and Classification.

ERIC Educational Resources Information Center

McCully, James S., Jr., Comp.

This publication, one of five sections, was developed for use in first and second year basic agriculture courses in secondary schools in Mississippi. The five lessons focus on the measurement and description of property and the classification of land. The purposes of the lessons are to (1) introduce the units and methods used to measure distance…

Use of geographic information systems for applications on gas pipeline rights-of-way

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sydelko, P.J.; Wilkey, P.L.

1992-12-01

Geographic information system (GIS) applications for the siting and monitoring of gas pipeline rights-of-way (ROWS) were developed for areas near Rio Vista, California. The data layers developed for this project represent geographic features, such as landcover, elevation, aspect, slope, soils, hydrography, transportation, endangered species, wetlands, and public line surveys. A GIS was used to develop and store spatial data from several sources; to manipulate spatial data to evaluate environmental and engineering issues associated with the siting, permitting, construction, maintenance, and monitoring of gas pipeline ROWS; and to graphically display analysis results. Examples of these applications include (1) determination of environmentallymore » sensitive areas, such as endangered species habitat, wetlands, and areas of highly erosive soils; (2) evaluation of engineering constraints, including shallow depth to bedrock, major hydrographic features, and shallow water table; (3) classification of satellite imagery for landuse/landcover that will affect ROWS; and (4) identification of alternative ROW corridors that avoid environmentally sensitive areas or areas with severe engineering constraints.« less

GIS least-cost analysis approach for siting gas pipeline ROWs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sydelko, P.J.; Wilkey, P.L.

1994-09-01

Geographic-information-system applications for the siting and monitoring of gas pipeline rights-of-way (ROWS) were developed for areas near Rio Vista, California. The data layers developed for this project represent geographic features, such as landcover, elevation, aspect, slope, soils, hydrography, transportation corridors, endangered species habitats, wetlands, and public line surveys. A geographic information system was used to develop and store spatial data from several sources; to manipulate spatial data to evaluate environmental and engineering issues associated with the siting, permitting, construction, maintenance, and monitoring of gas-pipeline ROWS; and to graphically display analysis results. Examples of these applications include (1) determination of environmentallymore » sensitive areas, such as endangered species habitat, wetlands, and areas of highly erosive soils; (2) evaluation of engineering constraints, including shallow depth to bedrock, major hydrographic features, and shallow water table; (3) classification of satellite imagery for landuse/landcover that will affect ROWS; and (4) identification of alternative ROW corridors that avoid environmentally sensitive areas or areas with severe engineering constraints.« less

Use of geographic information systems for applications on gas pipeline rights-of-way

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sydelko, P.J.

1993-10-01

Geographic information system (GIS) applications for the siting and monitoring of gas pipeline rights-of-way (ROWS) were developed for areas near Rio Vista, California. The data layers developed for this project represent geographic features, such as landcover, elevation, aspect, slope, soils, hydrography, transportation, endangered species, wetlands, and public line surveys. A GIS was used to develop and store spatial data from several sources; to manipulate spatial data to evaluate environmental and engineering issues associated with the siting, permitting, construction, maintenance, and monitoring of gas pipeline ROWS; and to graphically display analysis results. Examples of these applications include (1) determination of environmentallymore » sensitive areas, such as endangered species habitat, wetlands, and areas of highly erosive soils; (2) evaluation of engineering constraints, including shallow depth to bedrock, major hydrographic features, and shallow water table; (3) classification of satellite imagery for land use/landcover that will affect ROWS; and (4) identification of alternative ROW corridors that avoid environmentally sensitive areas or areas with severe engineering constraints.« less

Use of geographic information systems for applications on gas pipeline rights-of-way

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sydelko, P.J.; Wilkey, P.L.

1992-01-01

Geographic information system (GIS) applications for the siting and monitoring of gas pipeline rights-of-way (ROWS) were developed for areas near Rio Vista, California. The data layers developed for this project represent geographic features, such as landcover, elevation, aspect, slope, soils, hydrography, transportation, endangered species, wetlands, and public line surveys. A GIS was used to develop and store spatial data from several sources; to manipulate spatial data to evaluate environmental and engineering issues associated with the siting, permitting, construction, maintenance, and monitoring of gas pipeline ROWS; and to graphically display analysis results. Examples of these applications include (1) determination of environmentallymore » sensitive areas, such as endangered species habitat, wetlands, and areas of highly erosive soils; (2) evaluation of engineering constraints, including shallow depth to bedrock, major hydrographic features, and shallow water table; (3) classification of satellite imagery for landuse/landcover that will affect ROWS; and (4) identification of alternative ROW corridors that avoid environmentally sensitive areas or areas with severe engineering constraints.« less

A 40-foot static cone penetrometer

USGS Publications Warehouse

Beard, R.M.; Lee, H.J.

1982-01-01

The Navy needs a lightweight device for testing seafloor soils to sub bottom depths of 12 meters in water depths to 60 meters. To meet this need a quasistatic cone penetration device that uses water jetting to reduce friction on the cone rod has been developed. This device is called the XSP-40. The 5-ton XSP-40 stands 15 meters tall and pushes a standard 5-ton cone into the seafloor. It is remotely controlled with an electronic unit on the deck of the support vessel. All cone outputs are recorded directly as a function of penetration depth with a strip chart recorder. A full suite of gauges is provided. on the electronic unit for monitoring the XSP-40's performance during a test .. About 40 penetration tests have been performed with very good success. The XSP-40 was field tested in Norton Sound, off the west coast of Alaska. The general objective, in addition to evaluation of the device, was to gather geotechnical information on sediments that may be involved in processes potentially hazardous to offshore development. Four example penetration records are presented from gas charged sediment zones and areas near the Yukon River delta. In general it was determined that soil classification from cone data agreed well with classifications from core samples. Relative densities of the silt-sand to sandy-silt soils were usually very high. The significance of these results are discussed with respect to storm wave, liquefaction. It is concluded that the XSP-40 is a durable and reliable piece of equipment capable of achieving penetration beyond that possible when not using the water jet system.

Vineyard zonal management for grape quality assessment by combining airborne remote sensed imagery and soil sensors

NASA Astrophysics Data System (ADS)

Bonilla, I.; Martínez De Toda, F.; Martínez-Casasnovas, J. A.

2014-10-01

Vineyard variability within the fields is well known by grape growers, producing different plant responses and fruit characteristics. Many technologies have been developed in last recent decades in order to assess this spatial variability, including remote sensing and soil sensors. In this paper we study the possibility of creating a stable classification system that better provides useful information for the grower, especially in terms of grape batch quality sorting. The work was carried out during 4 years in a rain-fed Tempranillo vineyard located in Rioja (Spain). NDVI was extracted from airborne imagery, and soil conductivity (EC) data was acquired by an EM38 sensor. Fifty-four vines were sampled at véraison for vegetative parameters and before harvest for yield and grape analysis. An Isocluster unsupervised classification in two classes was performed in 5 different ways, combining NDVI maps individually, collectively and combined with EC. The target vines were assigned in different zones depending on the clustering combination. Analysis of variance was performed in order to verify the ability of the combinations to provide the most accurate information. All combinations showed a similar behaviour concerning vegetative parameters. Yield parameters classify better by the EC-based clustering, whilst maturity grape parameters seemed to give more accuracy by combining all NDVIs and EC. Quality grape parameters (anthocyanins and phenolics), presented similar results for all combinations except for the NDVI map of the individual year, where the results were poorer. This results reveal that stable parameters (EC or/and NDVI all-together) clustering outcomes in better information for a vineyard zonal management strategy.

Multitemporal analysis of Landsat images to detect land use land cover changes for monitoring soil sealing in the Nola area (Naples, Italy)

NASA Astrophysics Data System (ADS)

De Giglio, Michaela; Allocca, Maria; Franci, Francesca

2016-10-01

Land Use Land Cover Changes (LULCC) data provide objective information to support environmental policy, urban planning purposes and sustainable land development. Understanding of past land use/cover practices and current landscape patterns is critical to assess the effects of LULCC on the Earth system. Within the framework of soil sealing in Italy, the present study aims to assess the LULCC of the Nola area (Naples metropolitan area, Italy), relating to a thirty year period from 1984 to 2015. The urban sprawl affects this area causing the impervious surface increase, the loss in rural areas and landscape fragmentation. Located near Vesuvio volcano and crossed by artificial filled rivers, the study area is subject to landslide, hydraulic and volcanic risks. Landsat time series has been processed by means of the supervised per-pixel classification in order to produce multitemporal Land Use Land Cover maps. Then, post-classification comparison approach has been applied to quantify the changes occurring between 1984 and 2015, also analyzing the intermediate variations in 1999, namely every fifteen years. The results confirm the urban sprawl. The increase of the built-up areas mainly causes the habitat fragmentation and the agricultural land conversion of the Nola area that is already damaged by unauthorized disposal of urban waste. Moreover, considering the local risk maps, it was verified that some of the new urban areas were built over known hazardous sites. In order to limit the soil sealing, urgent measures and sustainable urban planning are required.

Hydropodelogy From the Pedon to the Landscape: Challenges and Accomplishments in the National Cooperative Soil Survey

NASA Astrophysics Data System (ADS)

Hammer, D.; Richardson, J.; Hempel, J.; Market, P.

2005-12-01

American pedology has focused on the National Cooperative Soil Survey. Primary responsibility rests with the U.S. Department of Agriculture. The primary goals, are legislatively mandated, are to map the country's soils, make interpretations, provide information to clients, maintain and market the soil survey. The first goal is near completion and focus is shifting to the other three. Concomitantly, American pedological science is being impacted by several conditions: technological advances; land use changes at unprecedented scales and magnitudes; a burgeoning population increasingly "separated" from the land; and a major emphasis in universities upon biological ("life") sciences at the DNA scale - as if soil, nutrients and water are not life essentials. Effects of the Flood of 1993 and Hurricane Katrina suggest that humans do not understand earth/climate interactions, particularly climatic extremes. Pedologists know the focus on soil classification and mapping was at the expense of understanding processes. Hydropedology is a holistic approach to understanding soil and geomorphic process in order to predict the impacts of perturbations. Water movement on and in the soil is the primary mechanism of distributing and altering sediments and chemicals (pedogenesis), and depends for its success upon understanding that the soil profile is the record of developmental history at that landscape site. Hydropedologists believe soil scientists can use pedons (point data) from appropriate locations from flownets in complex landscapes to extrapolate processes. This is the "pedotransfer function" concept. Technological advances are coupled with the existing soil survey information to create important soil-landscape interpretations at a variety of scales. Early results have been very successful. Quantification of soil systems can be classified broadly into three categories; hard data, soft data and tacit knowledge. "Hard data" are measured numbers, and include such attributes as pH, texture, cation exchange capacity and event-specific rainfall. "Soft data" include soil maps, SSURGO data and climate maps. Soft data are combinations of observations, measurements and inferences that produce maps and models at various scales. "Tacit knowledge" is human understanding that results from focused experience within a system. A skilled soil scientist with tacit knowledge specific to a particular region can combination hard and soft data to develop important and useful interpretations and predictions. Illustrations from natural and urban settings will be provided. Soils and climate are temporally and spatially variable at all scales. Soil systems respond differently to different climates and perturbations. For example, the recent pluvial period in the Prairie Pothole region is changing surface soil sodium concentrations and locations and sizes of discharge wetlands. This is a relatively short-term response to a regional climate shift. Climatic shift in Oxisol landscapes will have little effect on soil cations. To optimize soil interpretations, focus must be on quantifying region-specific "dynamic" soil, geomorphic and climatic attributes. Recognizing these needs, the National Cooperative Soil Survey will develop regional watershed projects that focus on quantifying soil-water relationships that can be used at a variety of scales.

Visual soil evaluation - future research requirements

NASA Astrophysics Data System (ADS)

Emmet-Booth, Jeremy; Forristal, Dermot; Fenton, Owen; Ball, Bruce; Holden, Nick

2017-04-01

A review of Visual Soil Evaluation (VSE) techniques (Emmet-Booth et al., 2016) highlighted their established utility for soil quality assessment, though some limitations were identified; (1) The examination of aggregate size, visible intra-porosity and shape forms a key assessment criterion in almost all methods, thus limiting evaluation to structural form. The addition of criteria that holistically examine structure may be desirable. For example, structural stability can be indicated using dispersion tests or examining soil surface crusting, while the assessment of soil colour may indirectly indicate soil organic matter content, a contributor to stability. Organic matter assessment may also indicate structural resilience, along with rooting, earthworm numbers or shrinkage cracking. (2) Soil texture may influence results or impeded method deployment. Modification of procedures to account for extreme texture variation is desirable. For example, evidence of compaction in sandy or single grain soils greatly differs to that in clayey soils. Some procedures incorporate separate classification systems or adjust deployment based on texture. (3) Research into impacts of soil moisture content on VSE evaluation criteria is required. Criteria such as rupture resistance and shape may be affected by moisture content. It is generally recommended that methods are deployed on moist soils and quantification of influences of moisture variation on results is necessary. (4) Robust sampling strategies for method deployment are required. Dealing with spatial variation differs between methods, but where methods can be deployed over large areas, clear instruction on sampling is required. Additionally, as emphasis has been placed on the agricultural production of soil, so the ability of VSE for exploring structural quality in terms of carbon storage, water purification and biodiversity support also requires research. References Emmet-Booth, J.P., Forristal. P.D., Fenton, O., Ball, B.C. & Holden, N.M. 2016. A review of visual soil evaluation techniques for soil structure. Soil Use and Management, 32, 623-634.

Mid Infrared Polarized Light Scattering; Applications for the Remote Detection of Chemical and Biological Contaminations

DTIC Science & Technology

1992-01-01

CLASSIFICATION 11. SECURITY CLASSIFICATION 19. SECURITY CLASSIFICATION 20. LIMITATION OF ABSTRACTI rnEHUC AGE OF ABSTRACTUNCLSIFIED UNCLASSIFIED UL NSN... ag . ;nst liquid chemical agent simulants SF96, DIMP, and DMMP on a soil surface. The crosshatched wavelengthi-angle domains are areas where the...WHITE ag WRIUT pE/pmv" I MAKE LINE DASHED "fl WRlE,(*WML1r LINE COLOR WHITE al2 ELSE 3 WIUrTE(*,jEJ/MVO MAKE LINE SOUD 244 CALL INThPr(ICOL.COL) I NEER

[Study on the polarized reflectance hyperspectral characteristics and models of typical saline soil in the west of Jilin Province, China].

PubMed

Han, Yang; Qin, Wei-chao; Wang, Ye-qiao

2014-06-01

In recent years, the area of saline soil in the west of Jilin Province expands increasingly, and soil quality is becoming more and more worsening, which not only caused great damage to the land resources, but also posed a huge threat to agricultural production and ecological environment. We combined with polarized and hyperspectral information to establish the general model and scientifically validated it. The results show that there is a strong relationship between the saline soil hyperspectral polarized information and its physicochemical property parameters, and with regularity. This paper has important theoretical significance for the mechanism of saline soil surface reflection, recognition and classification of saline soil and background, the utilization of soil polarization sensor and the development of quantitative remote sensing.

Suitability evaluation tool for lands (rice, corn and soybean) as mobile application

NASA Astrophysics Data System (ADS)

Rahim, S. E.; Supli, A. A.; Damiri, N.

2017-09-01

Evaluation of land suitability for special purposes e.g. for food crops is a must, a means to understand determining factors to be considered in the management of a land successfully. A framework for evaluating the land suitability for purposes in agriculture was first introduced by the Food and Agriculture Organization (FAO) in late 1970s. When using the framework manually, it is time consuming and not interesting for land users. Therefore, the authors have developed an effective tool by transforming the FAO framework into smart mobile application. This application is designed by using simple language for each factor and also by utilizing rule based system (RBS) algorithm. The factors involved are soil type, depth of soil solum, soil fertility, soil pH, drainage, risk of flood, etc. Suitability in this paper is limited to rice, corn and soybean. The application is found to be easier to understand and also could automatically determine the suitability of land. Usability testing was also conducted with 75 respondents. The results showed the usability was in "very good" classification. The program is urgently needed by the land managers, farmers, lecturers, students and government officials (planners) to help them more easily manage their land for a better future.

Identification and testing of early indicators for N leaching from urine patches.

PubMed

Vogeler, Iris; Cichota, Rogerio; Snow, Val

2013-11-30

Nitrogen leaching from urine patches has been identified as a major source of nitrogen loss under intensive grazing dairy farming. Leaching is notoriously variable, influenced by management, soil type, year-to-year variation in climate and timing and rate of urine depositions. To identify early indicators for the risk of N leaching from urine patches for potential usage in a precision management system, we used the simulation model APSIM (Agricultural Production Systems SIMulator) to produce an extensive N leaching dataset for the Waikato region of New Zealand. In total, nearly forty thousand simulation runs with different combinations of soil type and urine deposition times, in 33 different years, were done. The risk forecasting indicators were chosen based on their practicality: being readily measured on farm (soil water content, temperature and pasture growth) or that could be centrally supplied to farms (such as actual and forecast weather data). The thresholds of the early indicators that are used to forecast a period for high risk of N leaching were determined via classification and regression tree analysis. The most informative factors were soil temperature, pasture dry matter production, and average soil water content in the top soil over the two weeks prior to the urine N application event. Rainfall and air temperature for the two weeks following urine deposition were also important to fine-tune the predictions. The identified early indicators were then tested for their potential to predict the risk of N leaching in two typical soils from the Waikato region in New Zealand. The accuracy of the predictions varied with the number of indicators, the soil type and the risk level, and the number of correct predictions ranged from about 45 to over 90%. Further expansion and fine-tuning of the indicators and the development of a practical N risk tool based on these indicators is needed. Copyright © 2013 Elsevier Ltd. All rights reserved.

MODIS-based spatiotemporal patterns of soil moisture and evapotranspiration interactions in Tampa Bay urban watershed

NASA Astrophysics Data System (ADS)

Chang, Ni-Bin; Xuan, Zhemin; Wimberly, Brent

2011-09-01

Soil moisture and evapotranspiration (ET) is affected by both water and energy balances in the soilvegetation- atmosphere system, it involves many complex processes in the nexus of water and thermal cycles at the surface of the Earth. These impacts may affect the recharge of the upper Floridian aquifer. The advent of urban hydrology and remote sensing technologies opens new and innovative means to undertake eventbased assessment of ecohydrological effects in urban regions. For assessing these landfalls, the multispectral Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing images can be used for the estimation of such soil moisture change in connection with two other MODIS products - Enhanced Vegetation Index (EVI), Land Surface Temperature (LST). Supervised classification for soil moisture retrieval was performed for Tampa Bay area on the 2 kmx2km grid with MODIS images. Machine learning with genetic programming model for soil moisture estimation shows advances in image processing, feature extraction, and change detection of soil moisture. ET data that were derived by Geostationary Operational Environmental Satellite (GOES) data and hydrologic models can be retrieved from the USGS web site directly. Overall, the derived soil moisture in comparison with ET time series changes on a seasonal basis shows that spatial and temporal variations of soil moisture and ET that are confined within a defined region for each type of surfaces, showing clustered patterns and featuring space scatter plot in association with the land use and cover map. These concomitant soil moisture patterns and ET fluctuations vary among patches, plant species, and, especially, location on the urban gradient. Time series plots of LST in association with ET, soil moisture and EVI reveals unique ecohydrological trends. Such ecohydrological assessment can be applied for supporting the urban landscape management in hurricane-stricken regions.

A simulation study of the effects of land cover and crop type on sensing soil moisture with an orbital C-band radar

NASA Technical Reports Server (NTRS)

Dobson, M. C.; Ulaby, F. T.; Moezzi, S.; Roth, E.

1983-01-01

Simulated C-band radar imagery for a 124-km by 108-km test site in eastern Kansas is used to classify soil moisture. Simulated radar resolutions are 100 m by 100 m, 1 km by 1 km, and 3 km by 3 km, and each is processed using more than 23 independent samples. Moisture classification errors are examined as a function of land-cover distribution, field-size distribution, and local topographic relief for the full test site and also for subregions of cropland, urban areas, woodland, and pasture/rangeland. Results show that a radar resolution of 100 m by 100 m yields the most robust classification accuracies.

Wetland Hydrologic Connectivity to Downstream Waters: A Classification Approach and National Assessment

NASA Astrophysics Data System (ADS)

Leibowitz, S. G.; Hill, R. A.; Weber, M.; Jones, C., Jr.; Rains, M. C.; Creed, I. F.; Christensen, J.

2017-12-01

Connectivity has become a major focus of hydrological and ecological studies. Connectivity enhances fluxes among landscape features, whereas isolation eliminates or reduces such flows. Thus connectivity can be an important characteristic controlling ecosystem services. Hydrologic connectivity is particularly significant, since chemical and biological flows are often associated with water movement. Wetlands have many important functions, and the degree to which they are hydrologically connected influences the effect they have on downstream waters. Wetlands with high connectivity can serve as sources (e.g., net exporters of dissolved organic carbon), while those with low connectivity can function as sinks (e.g., net importers of suspended sediments). We developed a system to classify wetlands based on type, magnitude, and frequency of hydrologic connectivity with downstream waters. We determined type (riparian, non-riparian surface, and non-riparian subsurface) by considering soil and bedrock permeability. For magnitude, we developed indices to represent travel time based on Manning's kinematic and Darcy's equations. We used soil drainage class as an indicator of frequency. We also included an index that assesses relative level of anthropogenic impacts to connectivity (e.g., presence of canals and ditches and impervious surfaces). The classification system was designed to be applied at various spatial scales using available data. The system was applied to 4.7 million wetlands in the conterminous United States, using the National Land Cover Dataset and other nationally available geospatial data, and the resulting maps were assessed for patterns in wetland connectivity. While wetland connectivity was dominated by fast, frequent riparian connections nationally, distributions of connectivity were characteristic for each region. Consideration of these distributions of connectivity should promote better management of watershed functions such as flood control and water quality improvement.

Light and dark soils at the Apollo 16 landing site

NASA Technical Reports Server (NTRS)

Heymann, D.; Walton, J. R.; Jordan, J. L.; Lakatos, S.; Yaniv, A.

1975-01-01

Lunar soils are discussed within the framework of a three-group classification scheme. Group I comprises North Ray Crater soils, group II contains light soils, and group III is made up of dark soils. It is suggested that group I soils originated from the light friable unit, one of the three units inside North Ray Crater. Group II soils were probably derived from the light matrix breccia unit; group II soils are mixtures of materials from all three units. It is concluded that soils with group III properties have been at the surface continuously for long periods. Group II soils show a record of solar wind exposure in the distant past (i.e., they have large (Ar-40/Ar-36)T ratios). Thus the regolith at the Apollo 16 site, which was observed to have marked layers of dark against light soils, contains sizeable 'pockets' or horizons at depth which are the sources of the group II soils.

Taxonomic classification of soils using digital information from LANDSAT data. Huayllamarca and eucaliptus areas. M.S. Thesis - Bolivia Univ.

NASA Technical Reports Server (NTRS)

Quiroga, S. Q.

1977-01-01

The applicability of LANDSAT digital information to soil mapping is described. A compilation of all cartographic information and bibliography of the study area is made. LANDSAT MSS images on a scale of 1:250,000 are interpreted and a physiographic map with legend is prepared. The study area is inspected and a selection of the sample areas is made. A digital map of the different soil units is produced and the computer mapping units are checked against the soil units encountered in the field. The soil boundaries obtained by automatic mapping were not substantially changed by field work. The accuracy of the automatic mapping is rather high.

Implementing Safety Measures

EPA Pesticide Factsheets

Required risk mitigation measures for soil fumigants protect handlers, applicators, and bystanders from pesticide exposure. Measures include buffer zones, sign posting, good agricultural practices, restricted use pesticide classification, and FMPs.

Demonstration Results for the Phytoextraction of Lead-Contaminated Soil at the Twin Cities Army Ammunition Plant, Arden Hills, Minnesota

DTIC Science & Technology

2000-07-01

and leachate collection prior to approval of future phytoextraction at sites such as this. Lead Phytoremediation Demonstration 8-1...number) FIELD GROUP SUB-GROUP Phytoremediation of Lead-Contaminated Soil 19. ABSTRACT (Continue on reverse if necessary and identify by block number...editions are obsolete SECURITY CLASSIFICATION OF THIS PAGE Lead Phytoremediation Demonstration

DecoFungi: a web application for automatic characterisation of dye decolorisation in fungal strains.

PubMed

Domínguez, César; Heras, Jónathan; Mata, Eloy; Pascual, Vico

2018-02-27

Fungi have diverse biotechnological applications in, among others, agriculture, bioenergy generation, or remediation of polluted soil and water. In this context, culture media based on color change in response to degradation of dyes are particularly relevant; but measuring dye decolorisation of fungal strains mainly relies on a visual and semiquantitative classification of color intensity changes. Such a classification is a subjective, time-consuming and difficult to reproduce process. DecoFungi is the first, at least up to the best of our knowledge, application to automatically characterise dye decolorisation level of fungal strains from images of inoculated plates. In order to deal with this task, DecoFungi employs a deep-learning model, accessible through a user-friendly web interface, with an accuracy of 96.5%. DecoFungi is an easy to use system for characterising dye decolorisation level of fungal strains from images of inoculated plates.

IFIS Model-Plus: A Web-Based GUI for Visualization, Comparison and Evaluation of Distributed Flood Forecasts and Hindcasts

NASA Astrophysics Data System (ADS)

Krajewski, W. F.; Della Libera Zanchetta, A.; Mantilla, R.; Demir, I.

2017-12-01

This work explores the use of hydroinformatics tools to provide an user friendly and accessible interface for executing and assessing the output of realtime flood forecasts using distributed hydrological models. The main result is the implementation of a web system that uses an Iowa Flood Information System (IFIS)-based environment for graphical displays of rainfall-runoff simulation results for both real-time and past storm events. It communicates with ASYNCH ODE solver to perform large-scale distributed hydrological modeling based on segmentation of the terrain into hillslope-link hydrologic units. The cyber-platform also allows hindcast of model performance by testing multiple model configurations and assumptions of vertical flows in the soils. The scope of the currently implemented system is the entire set of contributing watersheds for the territory of the state of Iowa. The interface provides resources for visualization of animated maps for different water-related modeled states of the environment, including flood-waves propagation with classification of flood magnitude, runoff generation, surface soil moisture and total water column in the soil. Additional tools for comparing different model configurations and performing model evaluation by comparing to observed variables at monitored sites are also available. The user friendly interface has been published to the web under the URL http://ifis.iowafloodcenter.org/ifis/sc/modelplus/.

Influence of multi-source and multi-temporal remotely sensed and ancillary data on the accuracy of random forest classification of wetlands in northern Minnesota

USGS Publications Warehouse

Corcoran, Jennifer M.; Knight, Joseph F.; Gallant, Alisa L.

2013-01-01

Wetland mapping at the landscape scale using remotely sensed data requires both affordable data and an efficient accurate classification method. Random forest classification offers several advantages over traditional land cover classification techniques, including a bootstrapping technique to generate robust estimations of outliers in the training data, as well as the capability of measuring classification confidence. Though the random forest classifier can generate complex decision trees with a multitude of input data and still not run a high risk of over fitting, there is a great need to reduce computational and operational costs by including only key input data sets without sacrificing a significant level of accuracy. Our main questions for this study site in Northern Minnesota were: (1) how does classification accuracy and confidence of mapping wetlands compare using different remote sensing platforms and sets of input data; (2) what are the key input variables for accurate differentiation of upland, water, and wetlands, including wetland type; and (3) which datasets and seasonal imagery yield the best accuracy for wetland classification. Our results show the key input variables include terrain (elevation and curvature) and soils descriptors (hydric), along with an assortment of remotely sensed data collected in the spring (satellite visible, near infrared, and thermal bands; satellite normalized vegetation index and Tasseled Cap greenness and wetness; and horizontal-horizontal (HH) and horizontal-vertical (HV) polarization using L-band satellite radar). We undertook this exploratory analysis to inform decisions by natural resource managers charged with monitoring wetland ecosystems and to aid in designing a system for consistent operational mapping of wetlands across landscapes similar to those found in Northern Minnesota.

The ITE Land classification: Providing an environmental stratification of Great Britain.

PubMed

Bunce, R G; Barr, C J; Gillespie, M K; Howard, D C

1996-01-01

The surface of Great Britain (GB) varies continuously in land cover from one area to another. The objective of any environmentally based land classification is to produce classes that match the patterns that are present by helping to define clear boundaries. The more appropriate the analysis and data used, the better the classes will fit the natural patterns. The observation of inter-correlations between ecological factors is the basis for interpreting ecological patterns in the field, and the Institute of Terrestrial Ecology (ITE) Land Classification formalises such subjective ideas. The data inevitably comprise a large number of factors in order to describe the environment adequately. Single factors, such as altitude, would only be useful on a national basis if they were the only dominant causative agent of ecological variation.The ITE Land Classification has defined 32 environmental categories called 'land classes', initially based on a sample of 1-km squares in Great Britain but subsequently extended to all 240 000 1-km squares. The original classification was produced using multivariate analysis of 75 environmental variables. The extension to all squares in GB was performed using a combination of logistic discrimination and discriminant functions. The classes have provided a stratification for successive ecological surveys, the results of which have characterised the classes in terms of botanical, zoological and landscape features.The classification has also been applied to integrate diverse datasets including satellite imagery, soils and socio-economic information. A variety of models have used the structure of the classification, for example to show potential land use change under different economic conditions. The principal data sets relevant for planning purposes have been incorporated into a user-friendly computer package, called the 'Countryside Information System'.

Using ecological zones to increase the detail of Landsat classifications

NASA Technical Reports Server (NTRS)

Fox, L., III; Mayer, K. E.

1981-01-01

Changes in classification detail of forest species descriptions were made for Landsat data on 2.2 million acres in northwestern California. Because basic forest canopy structures may exhibit very similar E-M energy reflectance patterns in different environmental regions, classification labels based on Landsat spectral signatures alone become very generalized when mapping large heterogeneous ecological regions. By adding a seven ecological zone stratification, a 167% improvement in classification detail was made over the results achieved without it. The seven zone stratification is a less costly alternative to the inclusion of complex collateral information, such as terrain data and soil type, into the Landsat data base when making inventories of areas greater than 500,000 acres.

What is the story that soil tells us? Environmental and anthropogenic change

NASA Astrophysics Data System (ADS)

Shanskiy, Merrit; Kriiska, Aivar; Oras, Ester

2015-04-01

The archaeological studies have shown the evidence of human impact on soils functioning. On the other hand, the changed conditions of normal soil functioning will influence the human settlement in specific area. This study is part of a wider archaeological project on the environmental studies of the Kohtla Iron Age sacrificial site. To obtain a data about soil cover around historical finding some 1500 years ago, special sampling and research were carried out at the study site located in Kohtla Vanaküla, northeastern Estonia where a valuable collection of metal weapons and tools was discovered. The aim of current study was to analyze the site-specific soils to find out the connections between soil records and human mediated historical land degradation. Also, the site specific conditions were studied in order to understand its impact on archaeological artefacts and their preservation conditions. For the current investigation the soil sampling was carried out in July, 2014. The soils were described based on 20 soil pits. The site-specific soil morphological description was finalized and chemical analyses were performed at the laboratory of Soil Science and Agrochemistry, Estonian University of Life Science. Soil was air dried and passed through a 2- mm sieve. The chemical elements (P, K, Ca, Mg, Fe) were analyzed by using Mehlich 3 extraction by MP-AES analytical performance. Soil pH was measured from the soil suspension with 1M KCl. Ctot was analysed by dry combustion method in a vario MAX CNS elemental analyser (ELEMENTAR, Germany). Organic C was determined with elemental analyzer. According to World Reference Base for Soil Resources (WRB) classification system (FAO, 1998), the soil in the study area belongs to the soils subgroups of Gley soils on yellowish-grey calcareous till. The study area soil cover has strong anthropogenic influence due to different human activities. First, there are agricultural activities in the area. Although the region is currently exploited as grassland for animal grazing, it is known to have been ploughed in the past, resulting in amelioration of this soil type. Second, a result of surrounding oil-shale mining the status of groundwater has been changed as well.

What makes up marginal lands and how can it be defined and classified?

NASA Astrophysics Data System (ADS)

Ivanina, Vadym

2017-04-01

Definitions of marginal lands are often not explicit. The term "marginal" is not supported by either a precise definition or research to determine which lands fall into this category. To identify marginal lands terminology/methodology is used which varies between physical characteristics and the current land use of a site as basic perspective. The term 'Marginal' is most commonly followed by 'degraded' lands, and other widely used terms such as 'abandoned', 'idle', 'pasture', 'surplus agricultural land', 'Conservation Reserve Programme' (CRP)', 'barren and carbon-poor land', etc. Some terms are used synonymously. To the category of "marginal" lands are predominantly included lands which are excluded from cultivation due to economic infeasibility or physical restriction for growing conventional crops. Such sites may still have potential to be used for alternative agricultural practice, e.g. bioenergy feedstock production. The existing categorizing of marginal lands does not allow evaluating soil fertility potential or to define type and level of constrains for growing crops as the reason of a low practical value with regards to land use planning. A new marginal land classification has to be established and developed. This classification should be built on criteria of soil biophysical properties, ecologic, environment and climate handicaps for growing crops, be easy in use and of high practical value. The SEEMLA consortium made steps to build such a marginal land classification which is based on direct criteria depicting soil properties and constrains, and defining their productivity potential. By this classification marginal lands are divided into eleven categories: shallow rooting, low fertility, stony texture, sandy texture, clay texture, salinic, sodicic, acidic, overwet, eroded, and contaminated. The basis of this classification was taken criteria modified after and adapted from Regulation EU (1305)2013. To define an area of marginal lands with climate and economic limitations, SEEMLA established and implemented the term "area of land marginality" with a broader on marginal lands. This term includes marginal lands themselves, evaluation of climate constrains and economic efficiency to grow crops. This approach allows to define, categorize and classify marginal land by direct indicators of soil biophysical properties, ecologic and environment constrains, and provides additional evaluation of lands marginality with regards to suitability for growing crops based on climate criteria.

Soils and landforms from Fildes Peninsula and Ardley Island, Maritime Antarctica

NASA Astrophysics Data System (ADS)

Michel, Roberto F. M.; Schaefer, Carlos E. G. R.; López-Martínez, Jerónimo; Simas, Felipe N. B.; Haus, Nick W.; Serrano, Enrique; Bockheim, James G.

2014-11-01

Fildes Peninsula (F.P.) and Ardley Island (A.I.) are among the first ice-free areas in Maritime Antarctica. Since the last glacial retreat in this part of Antarctica (8000 to 5000 years BP), the landscape in these areas evolved under paraglacial to periglacial conditions, with pedogenesis marked by cryogenic processes. We carried out a detailed soil and geomorphology survey, with full morphological and analytical description for both areas; forty-eight soil profiles representing different landforms were sampled, analyzed and classified according to the U.S. Soil Taxonomy and the World Reference Base for Soil Resources (WRB). Soils are mostly turbic, moderately developed, with podzolization and strong phosphatization (chemical weathering of rock minerals and formation of amorphous Al and Fe minerals) in former ornithogenic sites while in areas with poor vegetation show typical features of cryogenic weathering. Nivation, solifluction, cryoturbation, frost weathering, ablation and surface erosion are widespread. The most represented landform system by surface in Fildes Peninsula is the periglacial one, and 15 different periglacial landforms types have been identified and mapped. These features occupy about 30% of the land surface, in which patterned ground and stone fields are the most common landforms. Other significant landforms as protalus lobes, rock glaciers or debris lobes indicate the extensive presence of permafrost. Soil variability was high, in terms of morphological, physical and chemical properties, due to varying lithic contributions and mixing of different rocks, as well as to different degrees of faunal influence. Three soil taxonomy orders were identified, whereas thirty four individual pedons were differentiated. Fildes Peninsula experiences a south-north gradient from periglacial to paraglacial conditions, and apparently younger soils and landforms are located close to the Collins Glacier. Arenosols/Entisols and Cryosols/Gelisols (frequently cryoturbic) are the most important soil classes; Leptosols/Entisols, Gleysols/Aquents and Cambisols/Inceptisols also occur, all with gelic properties, and with varying faunal influences. Both soil classification systems are adequate to distinguish the local pedogenesis processes. The WRB system is broader, since it was designed to be applied in all Polar Regions; the family classes adopted by the ST were effective in separating soils with important differences with regard to texture and gravel content, all important attributes accounting for the ecological succession and periglacial processes. An altitudinal organization of landforms and processes can be recognized from geomorphological mapping. Periglacial features are dominant above 50 m a.s.l. although are present at lower altitude.

From the Sea to the Mountains: A Soils and Geomorphology Field Tour of North Carolina USA

NASA Astrophysics Data System (ADS)

Lindbo, David L.; Vepraskas, Michael; Kleiss, Joseph

2015-04-01

During the course of this tour students are introduced to the wide variety of soils and landscapes found across the state of North Carolina. These soils will be representative of the land regions of the southeastern United States. The soils in parts of this region are some of the oldest in the U.S. and are among the least fertile. North Carolina is divided into three distinct land regions: Coastal Plain, Piedmont, and Blue Ridge Belt (mountains). This tour includes sites in all three of these regions. The book entitled Soil Systems of North Carolina gives complete information about the soils across North Carolina and serves as a reference about soils as well as the types of parent materials encountered on the tour. North Carolina soils vary in elevation from sea level near the coast to approximately 2000 m at Mt. Mitchell which is the highest peak in the eastern U.S. The soils and landscapes in this region are not static, but change in response to natural and human forces. The natural forces center around climatic factors such as hurricanes that bring high wind velocities and exceptionally large rainfall amounts (>50 cm/day). These cause erosion of our coast, massive flooding, migration of sand dunes, and contribute to landslides in the western portion of the state. All of these make living here a challenge. The state contains soils in the thermic, mesic, and frigid temperature regimes. You will examine soils in all three temperature regimes on this trip. The diversity of soils also affects land use. Issues with drainage, septic systems, compaction, landslides and urbanization are highlighted at appropriate sites throughout the tour. At each of the stops soil profile and landscape are examined. Detailed profile descriptions and analytical data are provided for each pedon to assist in classification. Selected objectives and discussion points for each stop are likewise provided in order to promote discussion and identify the principle reasons for making a site visit. The discussion points are used loosely, and we encourage students ask any questions that they would like to discuss. The tour has been offered to our students since 2002 and is now being expanded to be part of our REU (research education for undergraduates) program that will be offered for the first time later this year.

Monitoring the vernal advancement and retrogradation (green wave effect) of natural vegetation

NASA Technical Reports Server (NTRS)

Rouse, J. W., Jr. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Emphasis has been given to an inventory of land resource types and land use at the ten Great Plains Corridor test sites. A resource and land use classification system was developed which uses available soil survey information and interpretations from NASA obtained high flight aerial photography to locate discrete areas of similar rangeland vegetation. Existing classification systems, even those developed for use with remote sensor data, were found to be inadequate for this project. This system is expected to be of general use for remote sensing related to land use and management. It has specific applicability to any effort aimed at regional use of ERTS-1 MSS digital data products. A preliminary assessment of the relative importance of rangelands in the Great Plains Corridor states indicates that the value of the livestock industry supported by this resource exceeds 23 billion dollars. The development of a Rangeland Feed Conditions index for this region could be used by more than 400,000 farm and ranch operators involved in the production of more than 40% of the nation's beef and much of the country's grain.

Seasonal variation of carcass decomposition and gravesoil chemistry in a cold (Dfa) climate.

PubMed

Meyer, Jessica; Anderson, Brianna; Carter, David O

2013-09-01

It is well known that temperature significantly affects corpse decomposition. Yet relatively few taphonomy studies investigate the effects of seasonality on decomposition. Here, we propose the use of the Köppen-Geiger climate classification system and describe the decomposition of swine (Sus scrofa domesticus) carcasses during the summer and winter near Lincoln, Nebraska, USA. Decomposition was scored, and gravesoil chemistry (total carbon, total nitrogen, ninhydrin-reactive nitrogen, ammonium, nitrate, and soil pH) was assessed. Gross carcass decomposition in summer was three to seven times greater than in winter. Initial significant changes in gravesoil chemistry occurred following approximately 320 accumulated degree days, regardless of season. Furthermore, significant (p < 0.05) correlations were observed between ammonium and pH (positive correlation) and between nitrate and pH (negative correlation). We hope that future decomposition studies employ the Köppen-Geiger climate classification system to understand the seasonality of corpse decomposition, to validate taphonomic methods, and to facilitate cross-climate comparisons of carcass decomposition. © 2013 American Academy of Forensic Sciences.

Monitoring, analysis and classification of vegetation and soil data collected by a small and lightweight hyperspectral imaging system

NASA Astrophysics Data System (ADS)

Mönnig, Carsten

2014-05-01

The increasing precision of modern farming systems requires a near-real-time monitoring of agricultural crops in order to estimate soil condition, plant health and potential crop yield. For large sized agricultural plots, satellite imagery or aerial surveys can be used at considerable costs and possible time delays of days or even weeks. However, for small to medium sized plots, these monitoring approaches are cost-prohibitive and difficult to assess. Therefore, we propose within the INTERREG IV A-Project SMART INSPECTORS (Smart Aerial Test Rigs with Infrared Spectrometers and Radar), a cost effective, comparably simple approach to support farmers with a small and lightweight hyperspectral imaging system to collect remotely sensed data in spectral bands in between 400 to 1700nm. SMART INSPECTORS includes the whole remote sensing processing chain of small scale remote sensing from sensor construction, data processing and ground truthing for analysis of the results. The sensors are mounted on a remotely controlled (RC) Octocopter, a fixed wing RC airplane as well as on a two-seated Autogyro for larger plots. The high resolution images up to 5cm on the ground include spectra of visible light, near and thermal infrared as well as hyperspectral imagery. The data will be analyzed using remote sensing software and a Geographic Information System (GIS). The soil condition analysis includes soil humidity, temperature and roughness. Furthermore, a radar sensor is envisaged for the detection of geomorphologic, drainage and soil-plant roughness investigation. Plant health control includes drought stress, vegetation health, pest control, growth condition and canopy temperature. Different vegetation and soil indices will help to determine and understand soil conditions and plant traits. Additional investigation might include crop yield estimation of certain crops like apples, strawberries, pasture land, etc. The quality of remotely sensed vegetation data will be tested with ground truthing tools like a spectrometer, visual inspection and ground control panel. The soil condition will also be monitored with a wireless sensor network installed on the examined plots of interest. Provided with this data, a farmer can respond immediately to potential threats with high local precision. In this presentation, preliminary results of hyperspectral images of distinctive vegetation cover and soil on different pasture test plots are shown. After an evaluation period, the whole processing chain will offer farmers a unique, near real- time, low cost solution for small to mid-sized agricultural plots in order to easily assess crop and soil quality and the estimation of harvest. SMART INSPECTORS remotely sensed data will form the basis for an input in a decision support system which aims to detect crop related issues in order to react quickly and efficiently, saving fertilizer, water or pesticides.

Optimal mapping of site-specific multivariate soil properties.

PubMed

Burrough, P A; Swindell, J

1997-01-01

This paper demonstrates how geostatistics and fuzzy k-means classification can be used together to improve our practical understanding of crop yield-site response. Two aspects of soil are important for precision farming: (a) sensible classes for a given crop, and (b) their spatial variation. Local site classifications are more sensitive than general taxonomies and can be provided by the method of fuzzy k-means to transform a multivariate data set with i attributes measured at n sites into k overlapping classes; each site has a membership value mk for each class in the range 0-1. Soil variation is of interest when conditions vary over patches manageable by agricultural machinery. The spatial variation of each of the k classes can be analysed by computing the variograms of mk over the n sites. Memberships for each of the k classes can be mapped by ordinary kriging. Areas of class dominance and the transition zones between them can be identified by an inter-class confusion index; reducing the zones to boundaries gives crisp maps of dominant soil groups that can be used to guide precision farming equipment. Automation of the procedure is straightforward given sufficient data. Time variations in soil properties can be automatically incorporated in the computation of membership values. The procedures are illustrated with multi-year crop yield data collected from a 5 ha demonstration field at the Royal Agricultural College in Cirencester, UK.

Preliminary investigation of Large Format Camera photography utility in soil mapping and related agricultural applications

NASA Technical Reports Server (NTRS)

Pelletier, R. E.; Hudnall, W. H.

1987-01-01

The use of Space Shuttle Large Format Camera (LFC) color, IR/color, and B&W images in large-scale soil mapping is discussed and illustrated with sample photographs from STS 41-6 (October 1984). Consideration is given to the characteristics of the film types used; the photographic scales available; geometric and stereoscopic factors; and image interpretation and classification for soil-type mapping (detecting both sharp and gradual boundaries), soil parent material topographic and hydrologic assessment, natural-resources inventory, crop-type identification, and stress analysis. It is suggested that LFC photography can play an important role, filling the gap between aerial and satellite remote sensing.

Use of Large-Scale Multi-Configuration EMI Measurements to Characterize Subsurface Structures of the Vadose Zone.

NASA Astrophysics Data System (ADS)

Huisman, J. A.; Brogi, C.; Pätzold, S.; Weihermueller, L.; von Hebel, C.; Van Der Kruk, J.; Vereecken, H.

2017-12-01

Subsurface structures of the vadose zone can play a key role in crop yield potential, especially during water stress periods. Geophysical techniques like electromagnetic induction EMI can provide information about dominant shallow subsurface features. However, previous studies with EMI have typically not reached beyond the field scale. We used high-resolution large-scale multi-configuration EMI measurements to characterize patterns of soil structural organization (layering and texture) and their impact on crop productivity at the km2 scale. We collected EMI data on an agricultural area of 1 km2 (102 ha) near Selhausen (NRW, Germany). The area consists of 51 agricultural fields cropped in rotation. Therefore, measurements were collected between April and December 2016, preferably within few days after the harvest. EMI data were automatically filtered, temperature corrected, and interpolated onto a common grid of 1 m resolution. Inspecting the ECa maps, we identified three main sub-areas with different subsurface heterogeneity. We also identified small-scale geomorphological structures as well as anthropogenic activities such as soil management and buried drainage networks. To identify areas with similar subsurface structures, we applied image classification techniques. We fused ECa maps obtained with different coil distances in a multiband image and applied supervised and unsupervised classification methodologies. Both showed good results in reconstructing observed patterns in plant productivity and the subsurface structures associated with them. However, the supervised methodology proved more efficient in classifying the whole study area. In a second step, we selected hundred locations within the study area and obtained a soil profile description with type, depth, and thickness of the soil horizons. Using this ground truth data it was possible to assign a typical soil profile to each of the main classes obtained from the classification. The proposed methodology was effective in producing a high resolution subsurface model in a large and complex study area that extends well beyond the field scale.

Vegetation and soils

USGS Publications Warehouse

Burke, M.K.; King, S.L.; Eisenbies, M.H.; Gartner, D.

2000-01-01

Intro paragraph: Characterization of bottomland hardwood vegetation in relatively undisturbed forests can provide critical information for developing effective wetland creation and restoration techniques and for assessing the impacts of management and development. Classification is a useful technique in characterizing vegetation because it summarizes complex data sets, assists in hypothesis generation about factors influencing community variation, and helps refine models of community structure. Hierarchical classification of communities is particularly useful for showing relationships among samples (Gauche 1982).

Estimating dry grass residues using landscape integration analysis

NASA Technical Reports Server (NTRS)

Hart, Quinn J.; Ustin, Susan L.; Duan, Lian; Scheer, George

1993-01-01

The acreage of grassland and grassland-savannah is extensive in California, making direct measurement and assessment logistically impossible. Grasslands cover the entire Central Valley up to about 1200 m elevation in the Coast Range and Sierra Nevada Range. Kuchler's map shows 5.35 M ha grassland with an additional 3.87 M ha in Oak savannah. The goal of this study was to examine the use of high spectral resolution sensors to distinguish between dry grass and soil in remotely sensed images. Spectral features that distinguish soils and dry plant material in the shortwave infrared (SWIR) region are thought to be primarily caused by cellulose and lignin, biochemicals which are absent from soils or occur as breakdown products in humid substances that lack the narrow-band features. We have used spectral mixing analysis (SMA) combined with Geographic Information Systems (GIS) analysis to characterize plant communities and dry grass biomass. The GIS was used to overlay elevation maps, and vegetation maps, with the SMA results. The advantage of non-image data is that it provides an independent source of information for the community classification.

NDVI and Panchromatic Image Correlation Using Texture Analysis

DTIC Science & Technology

2010-03-01

6 Figure 5. Spectral reflectance of vegetation and soil from 0.4 to 1.1 mm (From Perry...should help the classification methods to be able to classify kelp. Figure 5. Spectral reflectance of vegetation and soil from 0.4 to 1.1 mm...1988). Image processing software for imaging spectrometry analysis. Remote Sensing of Enviroment , 24: 201–210. Perry, C., & Lautenschlager, L. F

High-Explosive Cratering a Frozen and Unfrozen Soils in Alaska

DTIC Science & Technology

1980-02-01

SAMPLES I DEPTH TO .... T 24 DATE HOLEIROUN - S]T AR ED adO~ ________ F __24_ad_2____________7 EL . ITHOE (4IQ1 ~.0oioy Section ChlofRrndotboelI a...MotorIoI. Bronco Dno 20 f t.D. FREDRICKSON DEPTH %WATER SAI.IPLE SOIL MAAX FEET .4CtENT NO LEGEND CLASSIFICATION IZE F G i Silty Sandy Gravel Brown, Frozen

Application of remote sensing in South Dakota to provide accurate inventories of agricultural crops, enhance contrast in photographic products, monitor rangeland habitat loss, map Aspen, and prepare hydrogeologic surveys

NASA Technical Reports Server (NTRS)

Myers, V. I. (Principal Investigator); Dalsted, K. J.; Best, R. G.; Smith, J. R.; Eidenshink, J. C.; Schmer, F. A.; Andrawis, A. S.; Rahn, P. H.

1977-01-01

The author has identified the following significant results. Digital analysis of LANDSAT CCT's indicated that two discrete spectral background zones occurred among the five soil zone. K-CLASS classification of corn revealed that accuracy increased when two background zones were used, compared to the classification of corn stratified by five soil zones. Selectively varying film type developer and development time produces higher contract in reprocessed imagery. Interpretation of rangeland and cropped land data from 1968 aerial photography and 1976 LANDSAT imagery indicated losses in rangeland habitat. Thermal imagery was useful in locating potential sources of sub-surface water and geothermal energy, estimating evapotranspiration, and inventorying the land.

Automated image processing of Landsat II digital data for watershed runoff prediction

NASA Technical Reports Server (NTRS)

Sasso, R. R.; Jensen, J. R.; Estes, J. E.

1977-01-01

Digital image processing of Landsat data from a 230 sq km area was examined as a possible means of generating soil cover information for use in the watershed runoff prediction of Kern County, California. The soil cover information included data on brush, grass, pasture lands and forests. A classification accuracy of 94% for the Landsat-based soil cover survey suggested that the technique could be applied to the watershed runoff estimate. However, problems involving the survey of complex mountainous environments may require further attention

Potential impacts of robust surface roughness indexes on DTM-based segmentation

NASA Astrophysics Data System (ADS)

Trevisani, Sebastiano; Rocca, Michele

2017-04-01

In this study, we explore the impact of robust surface texture indexes based on MAD (median absolute differences), implemented by Trevisani and Rocca (2015), in the unsupervised morphological segmentation of an alpine basin. The area was already object of a geomorphometric analysis, consisting in the roughness-based segmentation of the landscape (Trevisani et al. 2012); the roughness indexes were calculated on a high resolution DTM derived by means of airborne Lidar using the variogram as estimator. The calculated roughness indexes have been then used for the fuzzy clustering (Odeh et al., 1992; Burrough et al., 2000) of the basin, revealing the high informative geomorphometric content of the roughness-based indexes. However, the fuzzy clustering revealed a high fuzziness and a high degree of mixing between textural classes; this was ascribed both to the morphological complexity of the basin and to the high sensitivity of variogram to non-stationarity and signal-noise. Accordingly, we explore how the new implemented roughness indexes based on MAD affect the morphological segmentation of the studied basin. References Burrough, P.A., Van Gaans, P.F.M., MacMillan, R.A., 2000. High-resolution landform classification using fuzzy k-means. Fuzzy Sets and Systems 113, 37-52. Odeh, I.O.A., McBratney, A.B., Chittleborough, D.J., 1992. Soil pattern recognition with fuzzy-c-means: application to classification and soil-landform interrelationships. Soil Sciences Society of America Journal 56, 505-516. Trevisani, S., Cavalli, M. & Marchi, L. 2012, "Surface texture analysis of a high-resolution DTM: Interpreting an alpine basin", Geomorphology, vol. 161-162, pp. 26-39. Trevisani, S. & Rocca, M. 2015, "MAD: Robust image texture analysis for applications in high resolution geomorphometry", Computers and Geosciences, vol. 81, pp. 78-92.

Terrain-Moisture Classification Using GPS Surface-Reflected Signals

NASA Technical Reports Server (NTRS)

Grant, Michael S.; Acton, Scott T.; Katzberg, Stephen J.

2006-01-01

In this study we present a novel method of land surface classification using surface-reflected GPS signals in combination with digital imagery. Two GPS-derived classification features are merged with visible image data to create terrain-moisture (TM) classes, defined here as visibly identifiable terrain or landcover classes containing a surface/soil moisture component. As compared to using surface imagery alone, classification accuracy is significantly improved for a number of visible classes when adding the GPS-based signal features. Since the strength of the reflected GPS signal is proportional to the amount of moisture in the surface, use of these GPS features provides information about the surface that is not obtainable using visible wavelengths alone. Application areas include hydrology, precision agriculture, and wetlands mapping.

Distribution of global fallouts cesium-137 in taiga and tundra catenae at the Ob River basin

NASA Astrophysics Data System (ADS)

Semenkov, I. N.; Usacheva, A. A.; Miroshnikov, A. Yu.

2015-03-01

The classification of soil catenae at the Ob River basin is developed and applied. This classification reflects the diverse geochemical conditions that led to the formation of certain soil bodies, their combinations and the migration fields of chemical elements. The soil and geochemical diversity of the Ob River basin catenae was analyzed. The vertical and lateral distribution of global fallouts cesium-137 was studied using the example of the four most common catenae types in Western Siberia tundra and taiga. In landscapes of dwarf birches and dark coniferous forests on gleysols, cryosols, podzols, and cryic-stagnosols, the highest 137Cs activity density and specific activity are characteristic of the upper soil layer of over 30% ash, while the moss-grass-shrub cover is characterized by low 137Cs activity density and specific activity. In landscapes of dwarf birches and pine woods on podzols, the maximum specific activity of cesium-137 is typical for moss-grass-shrub cover, while the maximum reserves are concentrated in the upper soil layer of over 30% ash. Bog landscapes and moss-grass-shrub cover are characterized by a minimum activity of 137Cs, and its reserves in soil generally decrease exponentially with depth. The cesium-137 penetration depth increases in oligotrophic histosols from northern to middle taiga landscapes from 10-15 to 40 cm. 137Cs is accumulated in oligotrophic histosols for increases in pH from 3.3 to 4.0 and in concretionary interlayers of pisoplinthic-cryic-histic-stagnosols. Cryogenic movement, on the one hand, leads to burying organic layers enriched in 137Cs and, on the other hand, to deducing specific activity when mixed with low-active material from lower soil layers.

Vs30 mapping at selected sites within the Greater Accra Metropolitan Area

NASA Astrophysics Data System (ADS)

Nortey, Grace; Armah, Thomas K.; Amponsah, Paulina

2018-06-01

A large part of Accra is underlain by a complex distribution of shallow soft soils. Within seismically active zones, these soils hold the most potential to significantly amplify seismic waves and cause severe damage, especially to structures sited on soils lacking sufficient stiffness. This paper presents preliminary site classification for the Greater Accra Metropolitan Area of Ghana (GAMA), using experimental data from two-dimensional (2-D) Multichannel Analysis of Surface Wave (MASW) technique. The dispersive characteristics of fundamental mode Rayleigh type surface waves were utilized for imaging the shallow subsurface layers (approx. up to 30 m depth) by estimating the 1D (depth) and 2D (depth and surface location) shear wave velocities at 5 selected sites. The average shear wave velocity for 30 m depth (Vs30), which is critical in evaluating the site response of the upper 30 m, was estimated and used for the preliminary site classification of the GAM area, as per NEHRP (National Earthquake Hazards Reduction Program). Based on the Vs30 values obtained in the study, two common site types C, and D corresponding to shallow (>6 m < 30 m) weathered rock and deep (up 30 m thick) stiff soils respectively, have been identified within the study area. Lower velocity profiles are inferred for the residual soils (sandy to silty clays), derived from the Accraian Formation that lies mainly within Accra central. Stiffer soil sites lie to the north of Accra, and to the west near Nyanyano. The seismic response characteristics over the residual soils in the GAMA have become apparent using the MASW technique. An extensive site effect map and a more robust probabilistic seismic hazard analysis can now be efficiently built for the metropolis, by considering the site classes and design parameters obtained from this study.

A GIS-based fuzzy classification for mapping the agricultural soils for N-fertilizers use.

PubMed

Assimakopoulos, J H; Kalivas, D P; Kollias, V J

2003-06-20

Special attention should be paid to the choice of the proper N-fertilizer, in order to avoid a further acidification and degradation of acid soils and at the same time to improve nitrogen use efficiency and to limit the nitrate pollution of the ground waters. Therefore, the risk of leaching of the fertilizer and of the acidification of the soils must be considered prior to any N-fertilizer application. The application of N-fertilizers to the soil requires a good knowledge of the soil-fertilizer relationship, which those who are planning the fertilization policy and/or applying it might not have. In this study, a fuzzy classification methodology is presented for mapping the agricultural soils according to the kind and the rate of application of N-fertilizer that should be used. The values of pH, clay, sand and carbonates soil variables are estimated at each point of an area by applying geostatistical techniques. Using the pH values three fuzzy sets: "no-risk-acidification"; "low-risk-acidification"; and "high-risk-acidification" are produced and the memberships of each point to the three sets are estimated. Additionally, from the clay and sand values the membership grade to the fuzzy set "risk-of-leaching" is calculated. The parameters and their values, which are used for the construction of the fuzzy sets, are based on the literature, the existing knowledge and the experimentation, of the soil-fertilizer relationships and provide a consistent mechanism for mapping the soils according to the type of N-fertilizers that should be applied and the rate of applications. The maps produced can easily be interpreted and used by non-experts in the application of the fertilization policy at national, local and farm level. The methodology is presented through a case study using data from the Amfilochia area, west Greece.

Impact of training sets on classification of high-throughput bacterial 16s rRNA gene surveys

PubMed Central

Werner, Jeffrey J; Koren, Omry; Hugenholtz, Philip; DeSantis, Todd Z; Walters, William A; Caporaso, J Gregory; Angenent, Largus T; Knight, Rob; Ley, Ruth E

2012-01-01

Taxonomic classification of the thousands–millions of 16S rRNA gene sequences generated in microbiome studies is often achieved using a naïve Bayesian classifier (for example, the Ribosomal Database Project II (RDP) classifier), due to favorable trade-offs among automation, speed and accuracy. The resulting classification depends on the reference sequences and taxonomic hierarchy used to train the model; although the influence of primer sets and classification algorithms have been explored in detail, the influence of training set has not been characterized. We compared classification results obtained using three different publicly available databases as training sets, applied to five different bacterial 16S rRNA gene pyrosequencing data sets generated (from human body, mouse gut, python gut, soil and anaerobic digester samples). We observed numerous advantages to using the largest, most diverse training set available, that we constructed from the Greengenes (GG) bacterial/archaeal 16S rRNA gene sequence database and the latest GG taxonomy. Phylogenetic clusters of previously unclassified experimental sequences were identified with notable improvements (for example, 50% reduction in reads unclassified at the phylum level in mouse gut, soil and anaerobic digester samples), especially for phylotypes belonging to specific phyla (Tenericutes, Chloroflexi, Synergistetes and Candidate phyla TM6, TM7). Trimming the reference sequences to the primer region resulted in systematic improvements in classification depth, and greatest gains at higher confidence thresholds. Phylotypes unclassified at the genus level represented a greater proportion of the total community variation than classified operational taxonomic units in mouse gut and anaerobic digester samples, underscoring the need for greater diversity in existing reference databases. PMID:21716311

Leaching potential of chlorpyrifos in an Andisol and Entisol: adsorption-desorption and degradation studies

NASA Astrophysics Data System (ADS)

Mosquera-Vivas, Carmen; Walther Hansen, Eddy; Garcia-Santos, Glenda; Obregón-Neira, Nelson; Celis-Ossa, Raul Ernesto; González-Murillo, Carlos Alberto; Juraske, Ronnie; Hellweg, Stefanie; Guerrero-Dallos, Jairo Arturo

2017-04-01

Ecological status of tropical soils like high OC content and microbial activity plays a key role to reduce the leaching of insecticide chlorpyrifos through the soil profile and therefore into groundwater. We found that chlorpyrifos has "transitional" leaching potential (GUS values varied between 1.8 and 2.5) throughout the soil depth, which differs from the "nonleacher" classification for temperate soils as based on surface level t1/2 and Koc values from international databases. These findings provide strong evidence of the importance of estimating the transport parameters and insecticide concentrations in different soil layers, especially when the amount and type of OC content vary throughout the soil profile. We got to such conclusions after studying the soil profile structural composition of soil organic matter and the adsorption/desorption characteristics of the insecticide in two different soil profiles (Andisol and Entisol) under agriculture production using Fourier transform infrared spectroscopy, nuclear magnetic resonance, and batch analysis methods.

Determining crop residue type and class using satellite acquired data. M.S. Thesis Progress Report, Jun. 1990

NASA Technical Reports Server (NTRS)

Zhuang, Xin

1990-01-01

LANDSAT Thematic Mapper (TM) data for March 23, 1987 with accompanying ground truth data for the study area in Miami County, IN were used to determine crop residue type and class. Principle components and spectral ratioing transformations were applied to the LANDSAT TM data. One graphic information system (GIS) layer of land ownership was added to each original image as the eighth band of data in an attempt to improve classification. Maximum likelihood, minimum distance, and neural networks were used to classify the original, transformed, and GIS-enhanced remotely sensed data. Crop residues could be separated from one another and from bare soil and other biomass. Two types of crop residue and four classes were identified from each LANDSAT TM image. The maximum likelihood classifier performed the best classification for each original image without need of any transformation. The neural network classifier was able to improve the classification by incorporating a GIS-layer of land ownership as an eighth band of data. The maximum likelihood classifier was unable to consider this eighth band of data and thus, its results could not be improved by its consideration.

Regional yield predictions of malting barley by remote sensing and ancillary data

NASA Astrophysics Data System (ADS)

Weissteiner, Christof J.; Braun, Matthias; Kuehbauch, Walter

2004-02-01

Yield forecasts are of high interest to the malting and brewing industry in order to allow the most convenient purchasing policy of raw materials. Within this investigation, malting barley yield forecasts (Hordeum vulgare L.) were performed for typical growing regions in South-Western Germany. Multisensoral and multitemporal Remote Sensing data on one hand and ancillary meteorological, agrostatistical, topographical and pedological data on the other hand were used as input data for prediction models, which were based on an empirical-statistical modeling approach. Since spring barley production is depending on acreage and on the yield per area, classification is needed, which was performed by a supervised multitemporal classification algorithm, utilizing optical Remote Sensing data (LANDSAT TM/ETM+). Comparison between a pixel-based and an object-oriented classification algorithm was carried out. The basic version of the yield estimation model was conducted by means of linear correlation of Remote Sensing data (NOAA-AVHRR NDVI), CORINE land cover data and agrostatistical data. In an extended version meteorological data (temperature, precipitation, etc.) and soil data was incorporated. Both, basic and extended prediction systems, led to feasible results, depending on the selection of the time span for NDVI accumulation.

Remote sensing of Earth terrain

NASA Technical Reports Server (NTRS)

Kong, Jin AU; Shin, Robert T.; Nghiem, Son V.; Yueh, Herng-Aung; Han, Hsiu C.; Lim, Harold H.; Arnold, David V.

1990-01-01

Remote sensing of earth terrain is examined. The layered random medium model is used to investigate the fully polarimetric scattering of electromagnetic waves from vegetation. The model is used to interpret the measured data for vegetation fields such as rice, wheat, or soybean over water or soil. Accurate calibration of polarimetric radar systems is essential for the polarimetric remote sensing of earth terrain. A polarimetric calibration algorithm using three arbitrary in-scene reflectors is developed. In the interpretation of active and passive microwave remote sensing data from the earth terrain, the random medium model was shown to be quite successful. A multivariate K-distribution is proposed to model the statistics of fully polarimetric radar returns from earth terrain. In the terrain cover classification using the synthetic aperture radar (SAR) images, the applications of the K-distribution model will provide better performance than the conventional Gaussian classifiers. The layered random medium model is used to study the polarimetric response of sea ice. Supervised and unsupervised classification procedures are also developed and applied to synthetic aperture radar polarimetric images in order to identify their various earth terrain components for more than two classes. These classification procedures were applied to San Francisco Bay and Traverse City SAR images.

Soils Diversity in the Southwest of Iberian Peninsula

NASA Astrophysics Data System (ADS)

Ramírez, Beatriz; Fernández-Pozo, Luis; Cabezas, José; Alexandre Castanho, Rui; Loures, Luís

2017-04-01

Back in 1960 the Seventh International Congress of Soil Science has proposed to develop a World Soil Mapping at a scale of 1: 1000000, with a purpose of getting a systematic inventory of soils, and also to allow a transfer of experiences between different countries and institutions. The mapping process has been coordinated by the European Soil Bureau (ESBN) and the European Commission, along with the participation of the European Environment Agency (EEA) and the Food and Agriculture Organization of the United Nations (FAO), based on the classification proposed by the "World Reference Base for Soil Resource" (WRB, FAO, 1998). Throughout this mapping and helped by the European Soil Database (v2.0), a mapping of soils and their diversity, in the area under analysis on the present paper - EUROACE (Alentejo-Centro-Extremadura) in the Southwest of Iberian Peninsula - has been developed and assessed using Geographic Information Systems (GIS) and algorithms of diversity. The obtained results have shown that in this particularly territory it is possible to identify 12 Reference Soil Groups (RSG) at first level, and 26 at second level, predominating Regosols and Dystrict Regosols respectively, whereas in the Mediterranean Region (Biogeographical Regions of Europe, BGRE) are 22 and 71 correspondingly with predominant for Cambisols and Calcaric Cambisols. By the analysis and assessment of soil diversity, the Shannon Index (H') is lower in EUROACE (1,67 vs 2,42 and 2,52 vs 3,35 to first and second levels); the evenness (E) shows a more equal distribution in RSG at first level in the Mediterranean Region (0,70 vs 0,67) and lower at the second level (0,67 vs 0,77 in EUROACE). These results will enable the development of a more complete pedodiversity inventory in several other regions, and also as tools to the study of soil susceptibility which will allow not only to protect a very important part of European natural heritage, but also to take specific measures to increase a better land use and management, which leads to sustainability.

Soil chemistry and pollution study of a closed landfill site at Ampar Tenang, Selangor, Malaysia.

PubMed

Mohd Adnan, Siti Nur Syahirah Binti; Yusoff, Sumiani; Piaw, Chua Yan

2013-06-01

A total of 20 landfills are located in State of Selangor, Malaysia. This includes the Ampar Tenang landfill site, which was closed on 26 January 2010. It was reported that the landfill has been upgraded to a level I type of sanitary classification. However, the dumpsite area is not being covered according to the classification. In addition, municipal solid waste was dumped directly on top of the unlined natural alluvium formation. This does not only contaminate surface and subsurface soils, but also initiates the potential risk of groundwater pollution. Based on previous studies, the Ampar Tenang soil has been proven to no longer be capable of preventing pollution migration. In this study, metal concentrations of soil samples up to 30 m depth were analyzed based on statistical analysis. It is very significant because research of this type has not been carried out before. The subsurface soils were significantly polluted by arsenic (As), lead (Pb), iron (Fe), copper (Cu) and aluminium (Al). As and Pb exceeded the safe limit values of 5.90 mg/kg and 31.00 mg/kg, respectively, based on Provincial Sediment Quality Guidelines for Metals and the Interim Sediment Quality Values. Furthermore, only Cu concentrations showed a significantly decreasing trend with increasing depth. Most metals were found on clay-type soils based on the cluster analysis method. Moreover, the analysis also differentiates two clusters: cluster I-Pb, As, zinc, Cu, manganese, calcium, sodium, magnesium, potassium and Fe; cluster II-Al. Different clustering may suggest a different contamination source of metals.

Development of Tier 1 screening tool for soil and groundwater vulnerability assessment in Korea using classification algorithm in a neural network

NASA Astrophysics Data System (ADS)

Shin, K. H.; Kim, K. H.; Ki, S. J.; Lee, H. G.

2017-12-01

The vulnerability assessment tool at a Tier 1 level, although not often used for regulatory purposes, helps establish pollution prevention and management strategies in the areas of potential environmental concern such as soil and ground water. In this study, the Neural Network Pattern Recognition Tool embedded in MATLAB was used to allow the initial screening of soil and groundwater pollution based on data compiled across about 1000 previously contaminated sites in Korea. The input variables included a series of parameters which were tightly related to downward movement of water and contaminants through soil and ground water, whereas multiple classes were assigned to the sum of concentrations of major pollutants detected. Results showed that in accordance with diverse pollution indices for soil and ground water, pollution levels in both media were strongly modulated by site-specific characteristics such as intrinsic soil and other geologic properties, in addition to pollution sources and rainfall. However, classification accuracy was very sensitive to the number of classes defined as well as the types of the variables incorporated, requiring careful selection of input variables and output categories. Therefore, we believe that the proposed methodology is used not only to modify existing pollution indices so that they are more suitable for addressing local vulnerability, but also to develop a unique assessment tool to support decision making based on locally or nationally available data. This study was funded by a grant from the GAIA project(2016000560002), Korea Environmental Industry & Technology Institute, Republic of Korea.

A new approach for assessing integrated potential conditions of soil and climate for the cultivation of vines in the Azores Islands

NASA Astrophysics Data System (ADS)

Madruga, João; Azevedo, Eduardo; Reis, Francisco; Sampaio, João; Pinheiro, Jorge; Madeira, Manuel

2014-05-01

Being fairly common belief that the particular soil conditions are of great importance in defining the characteristics and qualities of the wine as the final product, it is also recognized the difficulty of establishing and interpreting this relationship clearly. The geological diversity seems to correlate with the characteristics defined in accordance with the classification system employed in France Appellation d' Origine Contrôlée (AOC), suggesting that, in addition to the variety and climate, geology and soil play an important role the properties and characteristics of the grapes produced in a given geographical location. Moreover, although it is known that the vine is tailored to a wide diversity of soil types, it appears also that many of the world's most famous vineyards are installed in poor and rocky terrain where no other crop would be grown in favorable conditions. Such is the case almost extreme implanted in the land of "cracker " and " Lagido " which are the traditional names in the archipelago of the Azores to the cracked surfaces of basaltic lava fields of heterogeneous size ranging from gravel to blocks of Azorean vineyards, whose vines manage to substrate cracks survival and production, albeit in modest yields. Apart from this traditional model of Azorean "terroir" of recognized cultural and landscape value where some interesting wines have been produced and quality recognized, there are significant areas in the islands whose soil and climate and physiographic characteristics suggest a potential for wine production that deserves to be the object of careful assessment, with a view to a possible study of integrated experimental basis. We refer specifically to landscape units of the lower area of some islands, in many cases presently devoted to pasture during the summer where productivity tends to be marginal, because strongly affected by water stress. Such areas preferably South exposed and of gentle slopes providing moderate exposure to the mechanization of farming operations, comprise weakly weathered vitric soils from pyroclastic materials, well drained, mainly over pomice deposits but also of basaltic "lapilli" which, according to the Soil Taxonomy classification generally fall in the greatgroup of Udivitrands. In this preliminary study, the edaphic, climatic and physiographic characteristics of the landscape are considered based on GIS tools, in order to define the distribution of the most representative landscape units with the greatest apparent potential for wine production in some islands of the Azores.

A Brief History of the Soil Science Society of America

NASA Astrophysics Data System (ADS)

Brevik, Eric C.

2013-04-01

The Soil Science Society of America (SSSA) was officially born on November 18, 1936 at the Mayflower Hotel in Washington, D.C. with Richard Bradfield as the first President. SSSA was created from the merger of the American Soil Survey Association and the Soils Section of American Society of Agronomy (ASA). Six sections were established: 1) physics, 2) chemistry, 3) microbiology, 4) fertility, 5) morphology, and 6) technology, and total membership was less than 200. The first issue of SSSA Journal, then called SSSA Proceedings, published 87 items totaling 526 pages. The first recorded bank balance for SSSA was at the end of the 1937-38 fiscal year, and showed the Society to be worth 1,300.03. The Soils Section of ASA became the official American section of the International Society of Soil Science in 1934, and the new SSSA inherited that distinction which it retains to this day. SSSA has grown significantly since those early days. The original six sections have grown to 11 divisions, and some of those divisions have changed their names to reflect changes occurring within soil science. For example, the original section 5, morphology, is now Division S05 - Pedology after spending many years under other names such as Division V - Soil Classification and Division S-5 - Soil Genesis, Morphology, and Classification. SSSA was incorporated in the State of Wisconsin, USA on 22 January, 1952. Several awards have been developed to recognize achievement in the field of soil science, including the SSSA Presidential Award, Don and Betty Kirkham Soil Physics Award, Emil Truog Soil Science Award, International Soil Science Award, Irrometer Professional Certification Service Award, L.R. Ahuja Ag Systems Modeling Award, Marion L. and Chrystie M. Jackson Soil Science Award, Soil Science Applied Research Award, Soil Science Distinguished Service Award, Soil Science Education Award, Soil Science Industry and Professional Leadership Award, Soil Science Research Award, and SSSA Early Career Professional Award. SSSA has also hosted the World Congress of Soil Science in 1960 and 2006. In 2010 SSSA membership was at 6,367, the third highest membership total in SSSA history. SSSAJ published 259 items totaling 2,201 pages. But unlike 1937, SSSAJ is no longer SSSA's only journal. In 2009 Journal of Environmental Quality published 272 items on 2,480 pages, Soil Survey Horizons (renamed Soil Horizons in 2012) published 26 items on 133 pages, Vadose Zone Journal published 116 items on 1,088 pages, and Journal of Natural Resources and Life Sciences Education published 48 items on 250 pages, giving Society journals a total of 721 items published on 6,132 pages. At the end of 2010 SSSA was worth 3,130,163. All of these numbers show significant achievement in the years since the Society's founding, but not all of those years have been rosy. For example, SSSA's membership dropped from an all-time high of 6,402 in 1985 to 5,319 in 2002 and the Society's net worth declined from 2,132,750 in 1999 to 984,866 in 2002. This period from the mid-1980s through the early 2000s has probably been the most challenging so far in SSSA's history. Many changes are also in store going into the future. Over the past few years SSSA has become increasingly independent from ASA. While the two societies (along with the Crop Science Society of America (CSSA)) still maintain close ties, the members of SSSA have expressed a desire to emphasize that soils are more than agronomic. One indication of this increasing independence can be seen in the annual meetings. SSSA met jointly with the Geological Society of America in 2008 and will meet with the Entomological Society of America in 2015. There are also plans for SSSA to meet independently of ASA and CSSA for the first time in 2018. Another indication is the recent rearrangement of the governing structures of ASA, CSSA, and SSSA.

Environmental Monitoring Networks Optimization Using Advanced Active Learning Algorithms

NASA Astrophysics Data System (ADS)

Kanevski, Mikhail; Volpi, Michele; Copa, Loris

2010-05-01

The problem of environmental monitoring networks optimization (MNO) belongs to one of the basic and fundamental tasks in spatio-temporal data collection, analysis, and modeling. There are several approaches to this problem, which can be considered as a design or redesign of monitoring network by applying some optimization criteria. The most developed and widespread methods are based on geostatistics (family of kriging models, conditional stochastic simulations). In geostatistics the variance is mainly used as an optimization criterion which has some advantages and drawbacks. In the present research we study an application of advanced techniques following from the statistical learning theory (SLT) - support vector machines (SVM) and the optimization of monitoring networks when dealing with a classification problem (data are discrete values/classes: hydrogeological units, soil types, pollution decision levels, etc.) is considered. SVM is a universal nonlinear modeling tool for classification problems in high dimensional spaces. The SVM solution is maximizing the decision boundary between classes and has a good generalization property for noisy data. The sparse solution of SVM is based on support vectors - data which contribute to the solution with nonzero weights. Fundamentally the MNO for classification problems can be considered as a task of selecting new measurement points which increase the quality of spatial classification and reduce the testing error (error on new independent measurements). In SLT this is a typical problem of active learning - a selection of the new unlabelled points which efficiently reduce the testing error. A classical approach (margin sampling) to active learning is to sample the points closest to the classification boundary. This solution is suboptimal when points (or generally the dataset) are redundant for the same class. In the present research we propose and study two new advanced methods of active learning adapted to the solution of MNO problem: 1) hierarchical top-down clustering in an input space in order to remove redundancy when data are clustered, and 2) a general method (independent on classifier) which gives posterior probabilities that can be used to define the classifier confidence and corresponding proposals for new measurement points. The basic ideas and procedures are explained by applying simulated data sets. The real case study deals with the analysis and mapping of soil types, which is a multi-class classification problem. Maps of soil types are important for the analysis and 3D modeling of heavy metals migration in soil and prediction risk mapping. The results obtained demonstrate the high quality of SVM mapping and efficiency of monitoring network optimization by using active learning approaches. The research was partly supported by SNSF projects No. 200021-126505 and 200020-121835.

Prediction of cadmium enrichment in reclaimed coastal soils by classification and regression tree

NASA Astrophysics Data System (ADS)

Ru, Feng; Yin, Aijing; Jin, Jiaxin; Zhang, Xiuying; Yang, Xiaohui; Zhang, Ming; Gao, Chao

2016-08-01

Reclamation of coastal land is one of the most common ways to obtain land resources in China. However, it has long been acknowledged that the artificial interference with coastal land has disadvantageous effects, such as heavy metal contamination. This study aimed to develop a prediction model for cadmium enrichment levels and assess the importance of affecting factors in typical reclaimed land in Eastern China (DFCL: Dafeng Coastal Land). Two hundred and twenty seven surficial soil/sediment samples were collected and analyzed to identify the enrichment levels of cadmium and the possible affecting factors in soils and sediments. The classification and regression tree (CART) model was applied in this study to predict cadmium enrichment levels. The prediction results showed that cadmium enrichment levels assessed by the CART model had an accuracy of 78.0%. The CART model could extract more information on factors affecting the environmental behavior of cadmium than correlation analysis. The integration of correlation analysis and the CART model showed that fertilizer application and organic carbon accumulation were the most important factors affecting soil/sediment cadmium enrichment levels, followed by particle size effects (Al2O3, TFe2O3 and SiO2), contents of Cl and S, surrounding construction areas and reclamation history.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brown, J.; Tedrow, J.C.F.

For more than three decades Kaye Everett conducted research on pedology, hydrology, geology, and ecology in virtually all major polar regions of the globe. A summary of the historical developments in polar pedology and Everett`s major pedological accomplishments collectively serve as an appropriate tribute to this outstanding polar scientist. Building on early work by Russian pedologists, investigation of polar soils began in earnest following World War II. Differing national and individual soil classifications emerged and efforts to unify them continue to the present. Everett`s early studies in both hemispheres reinforced the concepts that pedogenic gradients existed. He demonstrated a climaticmore » gradient of soil processes and distribution in the Arctic with calcification diminishing and alkali processes increasing in a northward direction. Starting in the early 1970s Everett applied his interest in soil morphology, genesis, mapping, and classification to geobotanical landscape approaches in arctic Alaska. Working closely with other ecologists, these approaches resulted in a series of geobotanical and terrain sensitivity studies and publications related to both ecosystem function and response of tundra to impacts of resource development. More recent investigations focused on the transport of air- and waterborne nutrients in arctic watershed. Specific results of Everett`s own research and his collaboration with American and Russian colleagues are discussed. 106 refs., 2 figs.« less

Case studies: Soil mapping using multiple methods

NASA Astrophysics Data System (ADS)

Petersen, Hauke; Wunderlich, Tina; Hagrey, Said A. Al; Rabbel, Wolfgang; Stümpel, Harald

2010-05-01

Soil is a non-renewable resource with fundamental functions like filtering (e.g. water), storing (e.g. carbon), transforming (e.g. nutrients) and buffering (e.g. contamination). Degradation of soils is meanwhile not only to scientists a well known fact, also decision makers in politics have accepted this as a serious problem for several environmental aspects. National and international authorities have already worked out preservation and restoration strategies for soil degradation, though it is still work of active research how to put these strategies into real practice. But common to all strategies the description of soil state and dynamics is required as a base step. This includes collecting information from soils with methods ranging from direct soil sampling to remote applications. In an intermediate scale mobile geophysical methods are applied with the advantage of fast working progress but disadvantage of site specific calibration and interpretation issues. In the framework of the iSOIL project we present here some case studies for soil mapping performed using multiple geophysical methods. We will present examples of combined field measurements with EMI-, GPR-, magnetic and gammaspectrometric techniques carried out with the mobile multi-sensor-system of Kiel University (GER). Depending on soil type and actual environmental conditions, different methods show a different quality of information. With application of diverse methods we want to figure out, which methods or combination of methods will give the most reliable information concerning soil state and properties. To investigate the influence of varying material we performed mapping campaigns on field sites with sandy, loamy and loessy soils. Classification of measured or derived attributes show not only the lateral variability but also gives hints to a variation in the vertical distribution of soil material. For all soils of course soil water content can be a critical factor concerning a succesful application of geophysical methods, e.g. GPR on wet loessy soils will result in a high attenuation of signals. Furthermore, with this knowledge we support the development of geophysical pedo-transfer-functions, i.e. the link between geophysical to soil parameters, which is active researched in another work package of the iSOIL project. Acknowledgement: iSOIL-Interactions between soil related sciences - Linking geophysics, soil science and digital soil mapping is a Collaborative Project (Grant Agreement number 211386) co-funded by the Research DG of the European Commission within the RTD activities of the FP7 Thematic Priority Environment.

Some insights on grassland health assessment based on remote sensing.

PubMed

Xu, Dandan; Guo, Xulin

2015-01-29

Grassland ecosystem is one of the largest ecosystems, which naturally occurs on all continents excluding Antarctica and provides both ecological and economic functions. The deterioration of natural grassland has been attracting many grassland researchers to monitor the grassland condition and dynamics for decades. Remote sensing techniques, which are advanced in dealing with the scale constraints of ecological research and provide temporal information, become a powerful approach of grassland ecosystem monitoring. So far, grassland health monitoring studies have mostly focused on different areas, for example, productivity evaluation, classification, vegetation dynamics, livestock carrying capacity, grazing intensity, natural disaster detecting, fire, climate change, coverage assessment and soil erosion. However, the grassland ecosystem is a complex system which is formed by soil, vegetation, wildlife and atmosphere. Thus, it is time to consider the grassland ecosystem as an entity synthetically and establish an integrated grassland health monitoring system to combine different aspects of the complex grassland ecosystem. In this review, current grassland health monitoring methods, including rangeland health assessment, ecosystem health assessment and grassland monitoring by remote sensing from different aspects, are discussed along with the future directions of grassland health assessment.

Some Insights on Grassland Health Assessment Based on Remote Sensing

PubMed Central

Xu, Dandan; Guo, Xulin

2015-01-01

Grassland ecosystem is one of the largest ecosystems, which naturally occurs on all continents excluding Antarctica and provides both ecological and economic functions. The deterioration of natural grassland has been attracting many grassland researchers to monitor the grassland condition and dynamics for decades. Remote sensing techniques, which are advanced in dealing with the scale constraints of ecological research and provide temporal information, become a powerful approach of grassland ecosystem monitoring. So far, grassland health monitoring studies have mostly focused on different areas, for example, productivity evaluation, classification, vegetation dynamics, livestock carrying capacity, grazing intensity, natural disaster detecting, fire, climate change, coverage assessment and soil erosion. However, the grassland ecosystem is a complex system which is formed by soil, vegetation, wildlife and atmosphere. Thus, it is time to consider the grassland ecosystem as an entity synthetically and establish an integrated grassland health monitoring system to combine different aspects of the complex grassland ecosystem. In this review, current grassland health monitoring methods, including rangeland health assessment, ecosystem health assessment and grassland monitoring by remote sensing from different aspects, are discussed along with the future directions of grassland health assessment. PMID:25643060

Use of geographic information systems for applications on gas pipeline rights-of-way. Final report, December 1989--December 1991

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thompson, P.J.

1991-12-01

Geographic information system (GIS) applications for the siting and monitoring of gas pipeline rights-of-way for this project (ROWs) were developed for areas near Rio Vista, California. The data layers developed for this project represent geographic features, such as landcover, elevation, aspect, slope, soils, hydrography, transportation, endangered species, wetlands, and public line surveys. A GIS was used to develop and store spatial data from several sources; to manipulate spatial data to evaluate environmental and engineering issues associated with the siting, permitting, construction, maintenance, and monitoring of gas pipeline ROWS; and to graphically display analysis results. Examples of these applications include (1)more » determination of environmentally sensitive areas, such as endangered species habitat, wetlands, and areas of highly erosive soils; (2) evaluation of engineering constraints, including shallow depth to bedrock, major hydrographic features, and shallow water table; (3) classification of satellite imagery for landuse/landcover that will affect ROWs; and (4) identification of alternative ROW corridors that avoid environmentally sensitive areas or areas with severe engineering constraints.« less

Use of geographic information systems for applications on gas pipeline rights-of-way

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thompson, P.J.

1991-12-01

Geographic information system (GIS) applications for the siting and monitoring of gas pipeline rights-of-way for this project (ROWs) were developed for areas near Rio Vista, California. The data layers developed for this project represent geographic features, such as landcover, elevation, aspect, slope, soils, hydrography, transportation, endangered species, wetlands, and public line surveys. A GIS was used to develop and store spatial data from several sources; to manipulate spatial data to evaluate environmental and engineering issues associated with the siting, permitting, construction, maintenance, and monitoring of gas pipeline ROWS; and to graphically display analysis results. Examples of these applications include (1)more » determination of environmentally sensitive areas, such as endangered species habitat, wetlands, and areas of highly erosive soils; (2) evaluation of engineering constraints, including shallow depth to bedrock, major hydrographic features, and shallow water table; (3) classification of satellite imagery for landuse/landcover that will affect ROWs; and (4) identification of alternative ROW corridors that avoid environmentally sensitive areas or areas with severe engineering constraints.« less

Habitat mapping using hyperspectral images in the vicinity of Hekla volcano in Iceland

NASA Astrophysics Data System (ADS)

Vilmundardóttir, Olga K.; Sigurmundsson, Friðþór S.; Pedersen, Gro B. M.; Falco, Nicola; Rustowicz, Rose; Gísladóttir, Guðrún; Benediktsson, Jón A.

2016-04-01

Hekla, one of the most active volcanoes in Iceland, has created a diverse volcanic landscape with lava flows, hyaloclastite and tephra fields. The variety of geological formations and different times of formation create diverse vegetation within Hekla's vicinity. The region is subjected to extensive loss of vegetation cover and soil erosion due to human utilization of woodlands and ongoing sheep grazing. The eolian activity and frequent tephra deposition has created vast areas of sparse vegetation cover. Over the 20th century, many activities have centered on preventing further loss of vegetated land and restoring ecosystems. The benefit of these activities is now noticeable in the increased vegetation and woodland cover although erosion is still active within the area. For mapping and monitoring this highly dynamic environment remote sensing techniques are extremely useful. One of the principal goals of the project 'Environmental Mapping and Monitoring of Iceland with Remote Sensing' (EMMIRS) is to use hyperspectral images and LiDAR data to classify and map the vegetation within the Hekla area. The data was collected in an aerial survey in summer 2015 by the Natural Environment Research Council (NERC), UK. The habitat type classification, currently being developed at the Icelandic Institute of Natural History and follows the structure of the EUNIS classification system, will be used for classifying the vegetation. The habitat map created by this new technique's outcome will be compared to the existent vegetation maps made by the conventional vegetation mapping method and the multispectral image classification techniques. In the field, vegetation cover, soil properties and spectral reflectance were measured within different habitat types. Special emphasis was on collecting data on vegetation and soil in the historical lavas from Hekla for assessing habitats forming over the millennia. A lava-chronosequence was established by measuring vegetation and soil in lavas formed in 2000, 1991, 1980-81, 1970, 1947, 1913, 1878, 1845, 1766-68, 1693, 1554, 1389-90, 1300, and 1206, representing surfaces of age 15-809 years. Results showed that vegetation cover established rather quickly on the lavas where mosses and lichens already created a full cover after 24 years. The cover remained stable and mosses were the dominant plant group for centuries, unless where tephra fall had occurred or where eolian deposition prevailed. The colonization of vascular plants on the lava was slow except at sites of eolian deposition and tephra fall. Dwarf shrubs and shrubs were rare or even absent on the lavas formed during the last century but their cover increased with increasing age of the lava fields. The older lava fields featured a variety of vegetation classes, indicating different rates and pathways of succession depending on altitude, proximity to eolian sources, land use and other factors. The many similarities yet big contrasts in the habitats featured within the Hekla region pose a challenge for creating a habitat map of the area, testing the potency of the hyperspectral data and classification techniques to the fullest.

Visual assessment of soil structure quality in an agroextractivist system in Southeastern Amazonia

NASA Astrophysics Data System (ADS)

Fernanda Simões da Silva, Laura; Stuchi Boschi, Raquel; Ortega Gomes, Matheus; Cooper, Miguel

2016-04-01

Soil structure is considered a key factor in the functioning of soil, affecting its ability to support plant and animal life, and moderate environmental quality. Numerous methods are available to evaluate soil structure based on physical, chemical and biological indicators. Among the physical indicators, the attributes most commonly used are soil bulk density, porosity, soil resistance to penetration, tensile strength of aggregates, soil water infiltration, and available water. However, these methods are expensive and generally time costly for sampling and laboratorial procedures. Recently, evaluations using qualitative and semi-quantitative indicators of soil structure quality have gained importance. Among these methods, the method known as Visual Evaluation of Soil Structure (VESS) (Ball et al., 2007; Guimarães et al., 2011) can supply this necessity in temperate and tropical regions. The study area is located in the Piranheira Praialta Agroextrativist Settlement Project in the county of Nova Ipixuna, Pará, Brazil. Two toposequences were chosen, one under native forest and the other under pasture. Pits were opened in different landscape positions (upslope, midslope and downslope) for soil morphological, micromorphological and physical characterization. The use of the soil visual evaluation method (SVE) consisted in collecting an undisturbed soil sample of approximately 25 cm in length, 20 cm in width and 10 cm in depth. 12 soil samples were taken for each land use. The samples were manually fragmented, respecting the fracture planes between the aggregates. The SVE was done comparing the fragmented sample with a visual chart and scores were given to the soil structure. The categories that define the soil structure quality (Qe) vary from 1 to 5. Lower scores mean better soil structure. The final score calculation was done using the classification key of Ball et al. (2007) adapted by Guimarães (2011). A change in soil structure was observed between forest and pasture. The presence of layers of different depths, and size and shape of aggregates resulted in a lower Qe in the forest soils (Qe= 2,04 ±0,4), followed by the pasture (Qe= 3,09 ± 1,3). These results indicate certain degradation in the soil structure in the pasture. The variability of the soil structure in the forest samples was lower. The pasture samples presented a worse soil structure when compared to the forest, although their Qe values can be considered good.

Spatial Dependence of Physical Attributes and Mechanical Properties of Ultisol in a Sugarcane Field.

PubMed

Tavares, Uilka Elisa; Rolim, Mário Monteiro; de Oliveira, Veronildo Souza; Pedrosa, Elvira Maria Regis; Siqueira, Glécio Machado; Magalhães, Adriana Guedes

2015-01-01

This study investigates the effect of conventional tillage and application of the monoculture of sugar cane on soil health. Variables like density, moisture, texture, consistency limits, and preconsolidation stress were taken as indicators of soil quality. The measurements were made at a 120 × 120 m field cropped with sugar cane under conventional tillage. The objective of this work was to characterize the soil and to study the spatial dependence of the physical and mechanical attributes. Then, undisturbed soil samples were collected to measure bulk density, moisture content and preconsolidation stress and disturbed soil samples for classification of soil texture, and consistency limits. The soil texture indicated that soil can be characterized as sandy clay soil and a sandy clay loam soil, and the consistency limits indicated that the soil presents an inorganic low plasticity clay. The preconsolidation tests tillage in soil moisture content around 19% should be avoided or should be chosen a management of soil with lighter vehicles in this moisture content, to avoid risk of compaction. Using geostatistical techniques mapping was possible to identify areas of greatest conservation soil and greater disturbance of the ground.

Spatial Dependence of Physical Attributes and Mechanical Properties of Ultisol in a Sugarcane Field

PubMed Central

Tavares, Uilka Elisa; Monteiro Rolim, Mário; Souza de Oliveira, Veronildo; Maria Regis Pedrosa, Elvira; Siqueira, Glécio Machado; Guedes Magalhães, Adriana

2015-01-01

This study investigates the effect of conventional tillage and application of the monoculture of sugar cane on soil health. Variables like density, moisture, texture, consistency limits, and preconsolidation stress were taken as indicators of soil quality. The measurements were made at a 120 × 120 m field cropped with sugar cane under conventional tillage. The objective of this work was to characterize the soil and to study the spatial dependence of the physical and mechanical attributes. Then, undisturbed soil samples were collected to measure bulk density, moisture content and preconsolidation stress and disturbed soil samples for classification of soil texture, and consistency limits. The soil texture indicated that soil can be characterized as sandy clay soil and a sandy clay loam soil, and the consistency limits indicated that the soil presents an inorganic low plasticity clay. The preconsolidation tests tillage in soil moisture content around 19% should be avoided or should be chosen a management of soil with lighter vehicles in this moisture content, to avoid risk of compaction. Using geostatistical techniques mapping was possible to identify areas of greatest conservation soil and greater disturbance of the ground. PMID:26167528

Wildlife management by habitat units: A preliminary plan of action

NASA Technical Reports Server (NTRS)

Frentress, C. D.; Frye, R. G.

1975-01-01

Procedures for yielding vegetation type maps were developed using LANDSAT data and a computer assisted classification analysis (LARSYS) to assist in managing populations of wildlife species by defined area units. Ground cover in Travis County, Texas was classified on two occasions using a modified version of the unsupervised approach to classification. The first classification produced a total of 17 classes. Examination revealed that further grouping was justified. A second analysis produced 10 classes which were displayed on printouts which were later color-coded. The final classification was 82 percent accurate. While the classification map appeared to satisfactorily depict the existing vegetation, two classes were determined to contain significant error. The major sources of error could have been eliminated by stratifying cluster sites more closely among previously mapped soil associations that are identified with particular plant associations and by precisely defining class nomenclature using established criteria early in the analysis.

Choice of resolution by functional trait or taxonomy affects allometric scaling in soil food webs.

PubMed

Sechi, Valentina; Brussaard, Lijbert; De Goede, Ron G M; Rutgers, Michiel; Mulder, Christian

2015-01-01

Belowground organisms often display a shift in their mass-abundance scaling relationships due to environmental factors such as soil chemistry and atmospheric deposition. Here we present new empirical data that show strong differences in allometric scaling according to whether the resolution at the local scale is based on a taxonomic or a functional classification, while only slight differences arise according to soil environmental conditions. For the first time, isometry (an inverse 1:1 proportion) is recognized in mass-abundance relationships, providing a functional signal for constant biomass distribution in soil biota regardless of discrete trophic levels. Our findings are in contrast to those from aquatic ecosystems, in that higher trophic levels in soil biota are not a direct function of increasing body mass.

How a national vegetation classification can help ecological research and management

USGS Publications Warehouse

Franklin, Scott; Comer, Patrick; Evens, Julie; Ezcurra, Exequiel; Faber-Langendoen, Don; Franklin, Janet; Jennings, Michael; Josse, Carmen; Lea, Chris; Loucks, Orie; Muldavin, Esteban; Peet, Robert K.; Ponomarenko, Serguei; Roberts, David G.; Solomeshch, Ayzik; Keeler-Wolf, Todd; Van Kley, James; Weakley, Alan; McKerrow, Alexa; Burke, Marianne; Spurrier, Carol

2015-01-01

The elegance of classification lies in its ability to compile and systematize various terminological conventions and masses of information that are unattainable during typical research projects. Imagine a discipline without standards for collection, analysis, and interpretation; unfortunately, that describes much of 20th-century vegetation ecology. With differing methods, how do we assess community dynamics over decades, much less centuries? How do we compare plant communities from different areas? The need for a widely applied vegetation classification has long been clear. Now imagine a multi-decade effort to assimilate hundreds of disparate vegetation classifications into one common classification for the US. In this letter, we introduce the US National Vegetation Classification (USNVC; www.usnvc.org) as a powerful tool for research and conservation, analogous to the argument made by Schimel and Chadwick (2013) for soils. The USNVC provides a national framework to classify and describe vegetation; here we describe the USNVC and offer brief examples of its efficacy.

Indigenous systems of forest classification: understanding land use patterns and the role of NTFPs in shifting cultivators' subsistence economies.

PubMed

Delang, Claudio O

2006-04-01

This article discusses the system of classification of forest types used by the Pwo Karen in Thung Yai Naresuan Wildlife Sanctuary in western Thailand and the role of nontimber forest products (NTFPs), focusing on wild food plants, in Karen livelihoods. The article argues that the Pwo Karen have two methods of forest classification, closely related to their swidden farming practices. The first is used for forest land that has been, or can be, swiddened, and classifies forest types according to growth conditions. The second system is used for land that is not suitable for cultivation and looks at soil properties and slope. The article estimates the relative importance of each forest type in what concerns the collection of wild food plants. A total of 134 wild food plant species were recorded in December 2004. They account for some 80-90% of the amount of edible plants consumed by the Pwo Karen, and have a base value of Baht 11,505 per year, comparable to the cash incomes of many households. The article argues that the Pwo Karen reliance on NTFPs has influenced their land-use and forest management practices. However, by restricting the length of the fallow period, the Thai government has caused ecological changes that are challenging the ability of the Karen to remain subsistence oriented. By ignoring shifting cultivators' dependence on such products, the involvement of governments in forest management, especially through restrictions imposed on swidden farming practices, is likely to have a considerable impact on the livelihood strategies of these communities.

Global digital data sets of soil type, soil texture, surface slope and other properties: Documentation of archived data tape

NASA Technical Reports Server (NTRS)

Staub, B.; Rosenzweig, C.; Rind, D.

1987-01-01

The file structure and coding of four soils data sets derived from the Zobler (1986) world soil file is described. The data were digitized on a one-degree square grid. They are suitable for large-area studies such as climate research with general circulation models, as well as in forestry, agriculture, soils, and hydrology. The first file is a data set of codes for soil unit, land-ice, or water, for all the one-degree square cells on Earth. The second file is a data set of codes for texture, land-ice, or water, for the same soil units. The third file is a data set of codes for slope, land-ice, or water for the same units. The fourth file is the SOILWRLD data set, containing information on soil properties of land cells of both Matthews' and Food and Agriculture Organization (FAO) sources. The fourth file reconciles land-classification differences between the two and has missing data filled in.

Vegetation cover and land use impacts on soil water repellency in an Urban Park located in Vilnius, Lithuania

NASA Astrophysics Data System (ADS)

Pereira, Paulo; Cerda, Artemi

2015-04-01

It is strongly recognized that vegetation cover, land use have important impacts on the degree of soil water repellency (SWR). Soil water repellency is a natural property of soils, but can be induced by natural and anthropogenic disturbances as fire and soil tillage (Doerr et al., 2000; Urbanek et al., 2007; Mataix-Solera et al., 2014). Urban parks are areas where soils have a strong human impact, with implications on their hydrological properties. The aim of this work is to study the impact of different vegetations cover and urban soils impact on SWR and the relation to other soil variables as pH, Electrical Conductivity (EC) and soil organic matter (SOM) in an urban park. The study area is located in Vilnius city (54°.68' N, 25°.25' E). It was collected 15 soil samples under different vegetation cover as Pine (Pinus Sylvestris), Birch (Alnus glutinosa), Penduculate Oak (Quercus robur), Platanus (Platanus orientalis) and other human disturbed areas as forest trails and soils collected from human planted grass. Soils were taken to the laboratory, air-dried at room temperature and sieved with the <2 mm mesh in order to remove the coarse material. Subsequently were placed in petri dishes and exposed to a controlled laboratory environment (temperature of 20C and 50% of air relative humidity) for one week to avoid potential impacts of the atmospheric conditions on SWR (Doerr, 1998). The persistence of SWR was measured using the water drop penetration time (WDPT) (Wessel, 1998). The classification of WDPT was according to Bisdom et al. (1993) <5 (wettable), 5-60 (slightly water repellent), 60-600 (strongly water repellent), 600-3600 (severely water repellent) and >3600 (extremely water repellent). The results showed significant differences among the different vegetation cover (Kruskal-Wallis H=20.64, p<0.001). The WDPT soil median values collected under Pine, Birch, Penduculate Oak, forest trails and soils from planted grass were significantly higher than Platanus soil. The soils from Pine, Birch, Penduculate Oak, forest trails and planted grass were majorly severely water repellent, while Platanus soils were mostly strong water repellent. Soil water repellency of Pine soils had a significant negative correlation with pH (-0.52, p<0.05) and a significant negative correlation with SOM (0.69, p<0.01) and EC (0.53, p<0.05). In relation to Birch soils, SWR had a significant negative correlation with pH (-0.88, p<0.001) and significant positive correlation with SOM (0.78, p<0.001). In relation to the other species no significant correlations were observed between SWR and pH, EC and SOM. Acknowledgments POSTFIRE (Soil quality, erosion control and plant cover recovery under different post-fire management scenarios, CGL2013-47862-C2-1-R), funded by the Spanish Ministry of Economy and Competitiveness; Fuegored; RECARE (Preventing and Remediating Degradation of Soils in Europe Through Land Care, FP7-ENV-2013-TWO STAGE), funded by the European Commission; and for the COST action ES1306 (Connecting European connectivity research). References Bisdom, E.B.A., Dekker, L., Schoute, J.F.Th. (1993) Water repellency of sieve fractions from sandy soils and relationships with organic material and soil structure. Geoderma, 56, 105-118. Doerr, S.H., Shakesby, R.A., Walsh, R.P.D. (2000) Soil water repellency: Its causes, characteristics and hydro-geomorphological significance. Earth-Science Reviews, 51, 33-65. Doerr, S.H. (1998) On standardising the "Water Drop Penetration Time" and the "Molarity of an Ethanol Droplet" techniques to classify soil hydrophobicity: a case study using medium textured soils. Earth Surface Process and Landforms, 23, 663-668. Mataix-Solera, J., Arcenegui, V., Zavala, L., Perez-Bejarano, A., Jordan, A., Morugan-Coronado, A., Barcenas-Moreno, G., Jimenez-Pinilla, P., Lozano, E., Granjed, A.J.P., Gil-Torres, J. (2014) Small variations of soil properties control fire induced water repellency, Spanish Journal of Soil Science, 4, 51-60. Urbanek., E., Hallet, P., Feeney, D., Horn, R. (2007) Water repellency and distribution of hydrophilic and hydrophobic compounds in soil aggregates from different tillage systems. Geoderma, 140, 147-155. Wessel, A.T. (1988) On using the effective contact angle and the water drop penetration time for classification of water repellency in dune soils. Earth Surface Process and Landforms, 13, 555-265.

Multi-discipline resource inventory of soils, vegetation and geology

NASA Technical Reports Server (NTRS)

Simonson, G. H. (Principal Investigator); Paine, D. P.; Lawrence, R. D.; Norgren, J. A.; Pyott, W. Y.; Herzog, J. H.; Murray, R. J.; Rogers, R.

1973-01-01

The author has identified the following significant results. Computer classification of natural vegetation, in the vicinity of Big Summit Prairie, Crook County, Oregon was carried out using MSS digital data. Impure training sets, representing eleven vegetation types plus water, were selected from within the area to be classified. Close correlations were visually observed between vegetation types mapped from the large scale photographs and the computer classification of the ERTS data (Frame 1021-18151, 13 August 1972).

Classification of Active Microwave and Passive Optical Data Based on Bayesian Theory and Mrf

NASA Astrophysics Data System (ADS)

Yu, F.; Li, H. T.; Han, Y. S.; Gu, H. Y.

2012-08-01

A classifier based on Bayesian theory and Markov random field (MRF) is presented to classify the active microwave and passive optical remote sensing data, which have demonstrated their respective advantages in inversion of surface soil moisture content. In the method, the VV, VH polarization of ASAR and all the 7 TM bands are taken as the input of the classifier to get the class labels of each pixel of the images. And the model is validated for the necessities of integration of TM and ASAR, it shows that, the total precision of classification in this paper is 89.4%. Comparing with the classification with single TM, the accuracy increase 11.5%, illustrating that synthesis of active and passive optical remote sensing data is efficient and potential in classification.

Preliminary Evaluation of TM for Soils Information

NASA Technical Reports Server (NTRS)

Thompson, D. R.; Henderson, K. E.; Houston, A. G.; Pitts, D. E.

1984-01-01

Thematic mapper data acquired over Mississippi County, Arkansas, were examined for utility in separating soil associations within generally level alluvium deposited by the Mississippi River. The 0.76 to 0.90 micron (Band 4) and the 1.55 to 1.75 micron (Band 5) were found to separate the different soil associations fairly well when compared to the USDA-SCS general soil map. The thermal channel also appeared to provide information at this level. A detailed soil survey was available at the field level along with ground observations of crop type, plant height, percent cover and growth stage. Soils within the fields ranged from uniform to soils that occur as patches of sand that stand out strongly against the intermingled areas of dark soil. Examination of the digital values of individual TM bands at the field level indicates that the influence of the soil is greater in TM than it was in MSS bands. The TM appears to provide greater detail of within field variability caused by soils than MSS and thus should provide improved information relating to crop and soil properties. However, this soil influence may cause crop identification classification procedures to have to account for the soil in their algorithms.

Mathematical models application for mapping soils spatial distribution on the example of the farm from the North of Udmurt Republic of Russia

NASA Astrophysics Data System (ADS)

Dokuchaev, P. M.; Meshalkina, J. L.; Yaroslavtsev, A. M.

2018-01-01

Comparative analysis of soils geospatial modeling using multinomial logistic regression, decision trees, random forest, regression trees and support vector machines algorithms was conducted. The visual interpretation of the digital maps obtained and their comparison with the existing map, as well as the quantitative assessment of the individual soil groups detection overall accuracy and of the models kappa showed that multiple logistic regression, support vector method, and random forest models application with spatial prediction of the conditional soil groups distribution can be reliably used for mapping of the study area. It has shown the most accurate detection for sod-podzolics soils (Phaeozems Albic) lightly eroded and moderately eroded soils. In second place, according to the mean overall accuracy of the prediction, there are sod-podzolics soils - non-eroded and warp one, as well as sod-gley soils (Umbrisols Gleyic) and alluvial soils (Fluvisols Dystric, Umbric). Heavy eroded sod-podzolics and gray forest soils (Phaeozems Albic) were detected by methods of automatic classification worst of all.

Revision of species inventory checklists for Sandia National Laboratories, Albuquerque, Bernalillo County, New Mexico

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fischer, N.T.

1990-10-01

This report revises and updates the 1974 report by W. C. Martin and W. L. Wagner, Biological Survey of Kirtland Air Force Base (East). The biological communities of Kirtland Air Force Base (KAFB) are described with respect to the Biome classification system of Brown (1982), and a standardized system of habitat types is proposed based on biome and soil type. The potential occurrence of state or federally endangered species is discussed. No species listed as endangered or threatened is known to occur on KAFB, although five are identified as potentially occurring. Updated lists of amphibians, reptiles, breeding birds, mammals, andmore » plants are presented. 18 refs., 3 figs., 8 tabs.« less

Description and classification of nonallophanic Andosols in south Ecuadorian alpine grasslands (páramo)

NASA Astrophysics Data System (ADS)

Buytaert, Wouter; Deckers, Jozef; Wyseure, Guido

2006-02-01

The páramo is a neotropical alpine ecosystem that covers more than 75,000 km 2 of the northern Andes of Colombia, Ecuador, Venezuela, and Peru. It provides important environmental services: more than 10 million people in the Andean highlands benefit from the water supply and regulation function, which is attributed to the volcanic soils that underlie the ecosystem. The soils are also major carbon sinks of global significance. Severe land use changes and soil degradation threaten both the hydrology and carbon sink function. Nevertheless, soil genesis and properties in the páramo is rather poorly understood, nor are their ecological functions well documented. The impact of the geomorphology of the páramo on soil genesis was studied in the rio Paute basin, south Ecuador. Two toposequences were described and analysed. In each toposequence, four pedons were selected representing summit, backslope, undrained plain situation, and valley bottom positions in the landscape. The soils are classified as Hydric Andosols in the World Reference Base for Soil Resources and Epiaquands or Hydrudands in Soil Taxonomy. They are very acidic and have a high organic matter content, high P deficiency, and Al toxicity. Their water content ranges from 2.64 g g - 1 at saturation, down to 1.24 g g - 1 at wilting point, resulting in a large water storage capacity. Two major soil forming processes are identified: (1) volcanic ash deposition and (2) accumulation of organic carbon. Volcanic ash deposits may vary in depth as a result of regional geomorphological factors such as parent material, orientation, slope, and altitude. Organic carbon accumulation is an interaction of both waterlogging, which depends on the position in the landscape, and the formation of organometallic complexes with Al and Fe released during volcanic ash breakdown. Despite the high variability in parent material and topography, the soil is characterised by a notable homogeneity in physico-chemical properties. Statistical analysis reveals that only topographic location has a slight but significant influence on soil pH as well as the organic matter content, saturated conductivity and water retention at high pressure. Finally, the exceptional properties of these soils provide useful insights to improve classification of the Andosols reference group of the FAO World reference Base for Soil Resources.

Effects of corn cob ash on lime stabilized lateritic soil

NASA Astrophysics Data System (ADS)

Nnochiri, Emeka Segun

2018-03-01

This study assesses the effects of Corn Cob Ash (CCA) on lime-stabilized lateritic soil. Preliminary tests were carried out on the natural soil sample for purpose of identification and classification. Lime being the main stabilizing material was thoroughly mixed with the soil sample to determine the optimum lime requirement of the sample as a basis for evaluating the effects of the CCA. The optimum lime requirement was 10%. The CCA was thereafter added to the lime stabilized soil in varying proportions of 2, 4, 6, 8 and 10%. Unsoaked CBR increased from 83% at 0% CCA to highest value of 94% at 4% CCA. Unconfined Compressive Strength (UCS) values increased from 1123kN/m2 at 0% CCA to highest value of 1180kN/m2 at 4% CCA. It was therefore concluded that CCA can serve as a good complement for lime stabilization in lateritic soil.

Utilization of ERTS data to detect plant diseases and nutrient deficiencies, soil types and moisture levels

NASA Technical Reports Server (NTRS)

Parks, W. L. (Principal Investigator); Sewell, J. I.; Hilty, J. W.; Rennie, J. C.

1973-01-01

The author has identified the following significant results. A significant finding to date is the delineation of the Memphis soil association in Obion County, Dyer County, and in portions of Kentucky. This soil association was delineated mechanically through the use of imagery in the digital tape format, appropriate computer software, and an IBM/360/05 computer. The Waverly-Swamp association as well as the Obion River have been identified on the ERTS-1 imagery as well as on the computer printout. These findings demonstrate the feasibility of delineating major soil associations through vegetative cover common to the association. Channel 7 provides the most information for studies of this type. Computer density printouts assist markedly in making density separations and delineating major soil moisture differences; however, signatures for soil moisture classification for this area of mixed land uses in relatively small tracts have not yet been developed.

Assimilation of Freeze - Thaw Observations into the NASA Catchment Land Surface Model

NASA Technical Reports Server (NTRS)

Farhadi, Leila; Reichle, Rolf H.; DeLannoy, Gabrielle J. M.; Kimball, John S.

2014-01-01

The land surface freeze-thaw (F-T) state plays a key role in the hydrological and carbon cycles and thus affects water and energy exchanges and vegetation productivity at the land surface. In this study, we developed an F-T assimilation algorithm for the NASA Goddard Earth Observing System, version 5 (GEOS-5) modeling and assimilation framework. The algorithm includes a newly developed observation operator that diagnoses the landscape F-T state in the GEOS-5 Catchment land surface model. The F-T analysis is a rule-based approach that adjusts Catchment model state variables in response to binary F-T observations, while also considering forecast and observation errors. A regional observing system simulation experiment was conducted using synthetically generated F-T observations. The assimilation of perfect (error-free) F-T observations reduced the root-mean-square errors (RMSE) of surface temperature and soil temperature by 0.206 C and 0.061 C, respectively, when compared to model estimates (equivalent to a relative RMSE reduction of 6.7 percent and 3.1 percent, respectively). For a maximum classification error (CEmax) of 10 percent in the synthetic F-T observations, the F-T assimilation reduced the RMSE of surface temperature and soil temperature by 0.178 C and 0.036 C, respectively. For CEmax=20 percent, the F-T assimilation still reduces the RMSE of model surface temperature estimates by 0.149 C but yields no improvement over the model soil temperature estimates. The F-T assimilation scheme is being developed to exploit planned operational F-T products from the NASA Soil Moisture Active Passive (SMAP) mission.

Using a spatial and tabular database to generate statistics from terrain and spectral data for soil surveys

USGS Publications Warehouse

Horvath , E.A.; Fosnight, E.A.; Klingebiel, A.A.; Moore, D.G.; Stone, J.E.; Reybold, W.U.; Petersen, G.W.

1987-01-01

A methodology has been developed to create a spatial database by referencing digital elevation, Landsat multispectral scanner data, and digitized soil premap delineations of a number of adjacent 7.5-min quadrangle areas to a 30-m Universal Transverse Mercator projection. Slope and aspect transformations are calculated from elevation data and grouped according to field office specifications. An unsupervised classification is performed on a brightness and greenness transformation of the spectral data. The resulting spectral, slope, and aspect maps of each of the 7.5-min quadrangle areas are then plotted and submitted to the field office to be incorporated into the soil premapping stages of a soil survey. A tabular database is created from spatial data by generating descriptive statistics for each data layer within each soil premap delineation. The tabular data base is then entered into a data base management system to be accessed by the field office personnel during the soil survey and to be used for subsequent resource management decisions.Large amounts of data are collected and archived during resource inventories for public land management. Often these data are stored as stacks of maps or folders in a file system in someone's office, with the maps in a variety of formats, scales, and with various standards of accuracy depending on their purpose. This system of information storage and retrieval is cumbersome at best when several categories of information are needed simultaneously for analysis or as input to resource management models. Computers now provide the resource scientist with the opportunity to design increasingly complex models that require even more categories of resource-related information, thus compounding the problem.Recently there has been much emphasis on the use of geographic information systems (GIS) as an alternative method for map data archives and as a resource management tool. Considerable effort has been devoted to the generation of tabular databases, such as the U.S. Department of Agriculture's SCS/S015 (Soil Survey Staff, 1983), to archive the large amounts of information that are collected in conjunction with mapping of natural resources in an easily retrievable manner.During the past 4 years the U.S. Geological Survey's EROS Data Center, in a cooperative effort with the Bureau of Land Management (BLM) and the Soil Conservation Service (SCS), developed a procedure that uses spatial and tabular databases to generate elevation, slope, aspect, and spectral map products that can be used during soil premapping. The procedure results in tabular data, residing in a database management system, that are indexed to the final soil delineations and help quantify soil map unit composition.The procedure was developed and tested on soil surveys on over 600 000 ha in Wyoming, Nevada, and Idaho. A transfer of technology from the EROS Data Center to the BLM will enable the Denver BLM Service Center to use this procedure in soil survey operations on BLM lands. Also underway is a cooperative effort between the EROS Data Center and SCS to define and evaluate maps that can be produced as derivatives of digital elevation data for 7.5-min quadrangle areas, such as those used during the premapping stage of the soil surveys mentioned above, the idea being to make such products routinely available.The procedure emphasizes the applications of digital elevation and spectral data to order-three soil surveys on rangelands, and will:Incorporate digital terrain and spectral data into a spatial database for soil surveys.Provide hardcopy products (that can be generated from digital elevation model and spectral data) that are useful during the soil pre-mapping process.Incorporate soil premaps into a spatial database that can be accessed during the soil survey process along with terrain and spectral data.Summarize useful quantitative information for soil mapping and for making interpretations for resource management.

Ecological site-based assessments of wind and water erosion: informing accelerated soil erosion management in rangelands

USGS Publications Warehouse

Webb, Nicholas P.; Herrick, Jeffrey E.; Duniway, Michael C.

2014-01-01

Accelerated soil erosion occurs when anthropogenic processes modify soil, vegetation or climatic conditions causing erosion rates at a location to exceed their natural variability. Identifying where and when accelerated erosion occurs is a critical first step toward its effective management. Here we explore how erosion assessments structured in the context of ecological sites (a land classification based on soils, landscape setting and ecological potential) and their vegetation states (plant assemblages that may change due to management) can inform systems for reducing accelerated soil erosion in rangelands. We evaluated aeolian horizontal sediment flux and fluvial sediment erosion rates for five ecological sites in southern New Mexico, USA, using monitoring data and rangeland-specific wind and water erosion models. Across the ecological sites, plots in shrub-encroached and shrub-dominated vegetation states were consistently susceptible to aeolian sediment flux and fluvial sediment erosion. Both processes were found to be highly variable for grassland and grass-succulent states across the ecological sites at the plot scale (0.25 Ha). We identify vegetation thresholds that define cover levels below which rapid (exponential) increases in aeolian sediment flux and fluvial sediment erosion occur across the ecological sites and vegetation states. Aeolian sediment flux and fluvial erosion in the study area can be effectively controlled when bare ground cover is 100 cm in length is less than ~35%. Land use and management activities that alter cover levels such that they cross thresholds, and/or drive vegetation state changes, may increase the susceptibility of areas to erosion. Land use impacts that are constrained within the range of natural variability should not result in accelerated soil erosion. Evaluating land condition against the erosion thresholds identified here will enable identification of areas susceptible to accelerated soil erosion and the development of practical management solutions.

Thousands of Viral Populations Recovered from Peatland Soil Metagenomes Reveal Viral Impacts on Carbon Cycling in Thawing Permafrost

NASA Astrophysics Data System (ADS)

Emerson, J. B.; Brum, J. R.; Roux, S.; Bolduc, B.; Woodcroft, B. J.; Singleton, C. M.; Boyd, J. A.; Hodgkins, S. B.; Wilson, R.; Trubl, G. G.; Jang, H. B.; Crill, P. M.; Chanton, J.; Saleska, S. R.; Rich, V. I.; Tyson, G. W.; Sullivan, M. B.

2016-12-01

Methane and carbon dioxide emissions, which are under significant microbial control, provide positive feedbacks to climate change in thawing permafrost peatlands. Although viruses in marine systems have been shown to impact microbial ecology and biogeochemical cycling through host cell lysis, horizontal gene transfer, and auxiliary metabolic gene expression, viral ecology in permafrost and other soils remains virtually unstudied due to methodological challenges. Here, we identified viral sequences in 208 assembled bulk soil metagenomes derived from a permafrost thaw gradient in Stordalen Mire, northern Sweden, from 2010-2012. 2,048 viral populations were recovered, which genome- and network-based classification revealed to be largely novel, increasing known viral genera globally by 40%. Ecologically, viral communities differed significantly across the thaw gradient and by soil depth. Co-occurring microbial community composition, soil moisture, and pH were predictors of viral community composition, indicative of biological and biogeochemical feedbacks as permafrost thaws. Host prediction—achieved through clustered regularly interspaced short palindromic repeats (CRISPRs), tetranucleotide frequency patterns, and other sequence similarities to binned microbial population genomes—was able to link 38% of the viral populations to a microbial host. 5% of the implicated hosts were archaea, predominantly methanogens and ammonia-oxidizing Nitrososphaera, 45% were Acidobacteria or Verrucomicrobia (mostly predicted heterotrophic complex carbon degraders), and 21% were Proteobacteria, including methane oxidizers. Recovered viral genome fragments also contained auxiliary metabolic genes involved in carbon and nitrogen cycling. Together, these data reveal multiple levels of previously unknown viral contributions to biogeochemical cycling, including to carbon gas emissions, in peatland soils undergoing and contributing to climate change. This work represents a significant step towards understanding viral roles in microbially-mediated biogeochemical cycling in soil.

Mapping soil heterogeneity using RapidEye satellite images

NASA Astrophysics Data System (ADS)

Piccard, Isabelle; Eerens, Herman; Dong, Qinghan; Gobin, Anne; Goffart, Jean-Pierre; Curnel, Yannick; Planchon, Viviane

2016-04-01

In the frame of BELCAM, a project funded by the Belgian Science Policy Office (BELSPO), researchers from UCL, ULg, CRA-W and VITO aim to set up a collaborative system to develop and deliver relevant information for agricultural monitoring in Belgium. The main objective is to develop remote sensing methods and processing chains able to ingest crowd sourcing data, provided by farmers or associated partners, and to deliver in return relevant and up-to-date information for crop monitoring at the field and district level based on Sentinel-1 and -2 satellite imagery. One of the developments within BELCAM concerns an automatic procedure to detect soil heterogeneity within a parcel using optical high resolution images. Such heterogeneity maps can be used to adjust farming practices according to the detected heterogeneity. This heterogeneity may for instance be caused by differences in mineral composition of the soil, organic matter content, soil moisture or soil texture. Local differences in plant growth may be indicative for differences in soil characteristics. As such remote sensing derived vegetation indices may be used to reveal soil heterogeneity. VITO started to delineate homogeneous zones within parcels by analyzing a series of RapidEye images acquired in 2015 (as a precursor for Sentinel-2). Both unsupervised classification (ISODATA, K-means) and segmentation techniques were tested. Heterogeneity maps were generated from images acquired at different moments during the season (13 May, 30 June, 17 July, 31 August, 11 September and 1 November 2015). Tests were performed using blue, green, red, red edge and NIR reflectances separately and using derived indices such as NDVI, fAPAR, CIrededge, NDRE2. The results for selected winter wheat, maize and potato fields were evaluated together with experts from the collaborating agricultural research centers. For a few fields UAV images and/or yield measurements were available for comparison.

Land Boundary Conditions for the Goddard Earth Observing System Model Version 5 (GEOS-5) Climate Modeling System: Recent Updates and Data File Descriptions

NASA Technical Reports Server (NTRS)

Mahanama, Sarith P.; Koster, Randal D.; Walker, Gregory K.; Takacs, Lawrence L.; Reichle, Rolf H.; De Lannoy, Gabrielle; Liu, Qing; Zhao, Bin; Suarez, Max J.

2015-01-01

The Earths land surface boundary conditions in the Goddard Earth Observing System version 5 (GEOS-5) modeling system were updated using recent high spatial and temporal resolution global data products. The updates include: (i) construction of a global 10-arcsec land-ocean lakes-ice mask; (ii) incorporation of a 10-arcsec Globcover 2009 land cover dataset; (iii) implementation of Level 12 Pfafstetter hydrologic catchments; (iv) use of hybridized SRTM global topography data; (v) construction of the HWSDv1.21-STATSGO2 merged global 30 arc second soil mineral and carbon data in conjunction with a highly-refined soil classification system; (vi) production of diffuse visible and near-infrared 8-day MODIS albedo climatologies at 30-arcsec from the period 2001-2011; and (vii) production of the GEOLAND2 and MODIS merged 8-day LAI climatology at 30-arcsec for GEOS-5. The global data sets were preprocessed and used to construct global raster data files for the software (mkCatchParam) that computes parameters on catchment-tiles for various atmospheric grids. The updates also include a few bug fixes in mkCatchParam, as well as changes (improvements in algorithms, etc.) to mkCatchParam that allow it to produce tile-space parameters efficiently for high resolution AGCM grids. The update process also includes the construction of data files describing the vegetation type fractions, soil background albedo, nitrogen deposition and mean annual 2m air temperature to be used with the future Catchment CN model and the global stream channel network to be used with the future global runoff routing model. This report provides detailed descriptions of the data production process and data file format of each updated data set.

Integrated terrain mapping with digital Landsat images in Queensland, Australia

USGS Publications Warehouse

Robinove, Charles Joseph

1979-01-01

Mapping with Landsat images usually is done by selecting single types of features, such as soils, vegetation, or rocks, and creating visually interpreted or digitally classified maps of each feature. Individual maps can then be overlaid on or combined with other maps to characterize the terrain. Integrated terrain mapping combines several terrain features into each map unit which, in many cases, is more directly related to uses of the land and to methods of land management than the single features alone. Terrain brightness, as measured by the multispectral scanners in Landsat 1 and 2, represents an integration of reflectance from the terrain features within the scanner's instantaneous field of view and is therefore more correlatable with integrated terrain units than with differentiated ones, such as rocks, soils, and vegetation. A test of the feasibilty of the technique of mapping integrated terrain units was conducted in a part of southwestern Queensland, Australia, in cooperation with scientists of the Queensland Department of Primary Industries. The primary purpose was to test the use of digital classification techniques to create a 'land systems map' usable for grazing land management. A recently published map of 'land systems' in the area (made by aerial photograph interpretation and ground surveys), which are integrated terrain units composed of vegetation, soil, topography, and geomorphic features, was used as a basis for comparison with digitally classified Landsat multispectral images. The land systems, in turn, each have a specific grazing capacity for cattle (expressed in beasts per km 2 ) which is estimated following analysis of both research results and property carrying capacities. Landsat images, in computer-compatible tape form, were first contrast-stretched to increase their visual interpretability, and digitally classified by the parallelepiped method into distinct spectral classes to determine their correspondence to the land systems classes and to areally smaller, but readily recognizable, 'land units.' Many land systems appeared as distinct spectral classes or as acceptably homogeneous combinations of several spectral classes. The digitally classified map corresponded to the general geographic patterns of many of the land systems. Statistical correlation of the digitally classified map and the published map was not possible because the published map showed only land systems whereas the digitally classified map showed some land units as well as systems. The general correspondence of spectral classes to the integrated terrain units means that the digital mapping of the units may precede fieldwork and act as a guide to field sampling and detailed terrain unit description as well as measuring of the location, area, and extent of each unit. Extension of the Landsat mapping and classification technique to other arid and semi-arid regions of the world may be feasible.

Review of Land Use and Land Cover Change research progress

NASA Astrophysics Data System (ADS)

Chang, Yue; Hou, Kang; Li, Xuxiang; Zhang, Yunwei; Chen, Pei

2018-02-01

Land Use and Land Cover Change (LUCC) can reflect the pattern of human land use in a region, and plays an important role in space soil and water conservation. The study on the change of land use patterns in the world is of great significance to cope with global climate change and sustainable development. This paper reviews the main research progress of LUCC at home and abroad, and suggests that land use change has been shifted from land use planning and management to land use change impact and driving factors. The development of remote sensing technology provides the basis and data for LUCC with dynamic monitoring and quantitative analysis. However, there is no uniform standard for land use classification at present, which brings a lot of inconvenience to the collection and analysis of land cover data. Globeland30 is an important milestone contribution to the study of international LUCC system. More attention should be paid to the accuracy and results contrasting test of land use classification obtained by remote sensing technology.

Predicting of soil erosion with regarding to rainfall erosivity and soil erodibility

NASA Astrophysics Data System (ADS)

Suif, Zuliziana; Razak, Mohd Amirun Anis Ab; Ahmad, Nordila

2018-02-01

The soil along the hill and slope are wearing away due to erosion and it can take place due to occurrence of weak and heavy rainfall. The aim of this study is to predict the soil erosion degree in Universiti Pertahanan Nasional Malaysia (UPNM) area focused on two major factor which is soil erodibility and rainfall erosivity. Soil erodibility is the possibilities of soil to detach and carried away during rainfall and runoff. The "ROM" scale was used in this study to determine the degree of soil erodibility, namely low, moderate, high, and very high. As for rainfall erosivity, the erosive power caused by rainfall that cause soil loss. A daily rainfall data collected from January to April was analyzed by using ROSE index classification to identify the potential risk of soil erosion. The result shows that the soil erodibilty are moderate at MTD`s hill, high at behind of block Lestari and Landslide MTD hill, and critical at behind the mess cadet. While, the highest rainfall erosivity was recorded in March and April. Overall, this study would benefit the organization greatly in saving cost in landslide protection as relevant authorities can take early measures repairing the most affected area of soil erosion.

A novel way to rapidly monitor microplastics in soil by hyperspectral imaging technology and chemometrics.

PubMed

Shan, Jiajia; Zhao, Junbo; Liu, Lifen; Zhang, Yituo; Wang, Xue; Wu, Fengchang

2018-07-01

Hyperspectral imaging technology has been investigated as a possible way to detect microplastics contamination in soil directly and efficiently in this study. Hyperspectral images with wavelength range between 400 and 1000 nm were obtained from soil samples containing different materials including microplastics, fresh leaves, wilted leaves, rocks and dry branches. Supervised classification algorithms such as support vector machine (SVM), mahalanobis distance (MD) and maximum likelihood (ML) algorithms were used to identify microplastics from the other materials in hyperspectral images. To investigate the effect of particle size and color, white polyethylene (PE) and black PE particles extracted from soil with two different particle size ranges (1-5 mm and 0.5-1 mm) were studied in this work. The results showed that SVM was the most applicable method for detecting white PE in soil, with the precision of 84% and 77% for PE particles in size ranges of 1-5 mm and 0.5-1 mm respectively. The precision of black PE detection achieved by SVM were 58% and 76% for particles of 1-5 mm and 0.5-1 mm respectively. Six kinds of household polymers including drink bottle, bottle cap, rubber, packing bag, clothes hanger and plastic clip were used to validate the developed method, and the classification precision of polymers were obtained from 79% to 100% and 86%-99% for microplastics particle 1-5 mm and 0.5-1 mm respectively. The results indicate that hyperspectral imaging technology is a potential technique to determine and visualize the microplastics with particle size from 0.5 to 5 mm on soil surface directly. Copyright © 2018 Elsevier Ltd. All rights reserved.

Assessment of Soil Environmental Quality in Huangguoshu Waterfalls Scenic Area

NASA Astrophysics Data System (ADS)

Luo, Rongbin; Feng, Kaiyu; Gu, Bo; Xu, Chengcheng

2018-03-01

This paper concentrates on five major heavy metal pollutants as soil environmental quality evaluation factors, respectively Lead (Pb), Cadmium (Cd), Mercury (Hg), Arsenic (As), Chromium (Cr), based on the National Soil Environmental Quality Standards (GB15618 - 1995), we used single factor index evaluation model of soil environmental quality and comprehensive index evaluation model to analyze surface soil environmental quality in the Huangguoshu Waterfalls scenic area. Based on surface soil analysis, our results showed that the individual contamination index, Pb, Hg, As and Cr in the Huangguoshu Waterfalls scenic area met class I according to requirements of National Soil Environmental Quality Standards, which indicated that Pb, Hg, As and Cr were not main heavy metal pollutants in this area, but the individual contamination index of Cd in soil was seriously exceeded National Soil Environmental Quality Standards’ requirement. Soil environmental quality in Shitouzhai, Luoshitan, Langgong Hongyan Power Plant have exceeded the requirement of National Soil Environmental Quality Standards “0.7< Pc≤ 1.0” (Alert Level), these soils had been slightly polluted; the classification of soil environmental quality assessment in Longgong downstream area was above “Alert Level”, it indicated that soil in this area was not polluted. Above all, relevant measures for soil remediation are put forward.

A higher-level classification of the Pannonian and western Pontic steppe grasslands (Central and Eastern Europe).

PubMed

Willner, Wolfgang; Kuzemko, Anna; Dengler, Jürgen; Chytrý, Milan; Bauer, Norbert; Becker, Thomas; Biţă-Nicolae, Claudia; Botta-Dukát, Zoltán; Čarni, Andraž; Csiky, János; Igić, Ruzica; Kącki, Zygmunt; Korotchenko, Iryna; Kropf, Matthias; Krstivojević-Ćuk, Mirjana; Krstonošić, Daniel; Rédei, Tamás; Ruprecht, Eszter; Schratt-Ehrendorfer, Luise; Semenishchenkov, Yuri; Stančić, Zvjezdana; Vashenyak, Yulia; Vynokurov, Denys; Janišová, Monika

2017-01-01

What are the main floristic patterns in the Pannonian and western Pontic steppe grasslands? What are the diagnostic species of the major subdivisions of the class Festuco-Brometea (temperate Euro-Siberian dry and semi-dry grasslands)? Carpathian Basin (E Austria, SE Czech Republic, Slovakia, Hungary, Romania, Slovenia, N Croatia and N Serbia), Ukraine, S Poland and the Bryansk region of W Russia. We applied a geographically stratified resampling to a large set of relevés containing at least one indicator species of steppe grasslands. The resulting data set of 17 993 relevés was classified using the TWINSPAN algorithm. We identified groups of clusters that corresponded to the class Festuco-Brometea . After excluding relevés not belonging to our target class, we applied a consensus of three fidelity measures, also taking into account external knowledge, to establish the diagnostic species of the orders of the class. The original TWINSPAN divisions were revised on the basis of these diagnostic species. The TWINSPAN classification revealed soil moisture as the most important environmental factor. Eight out of 16 TWINSPAN groups corresponded to Festuco-Brometea . A total of 80, 32 and 58 species were accepted as diagnostic for the orders Brometalia erecti , Festucetalia valesiacae and Stipo-Festucetalia pallentis , respectively. In the further subdivision of the orders, soil conditions, geographic distribution and altitude could be identified as factors driving the major floristic patterns. We propose the following classification of the Festuco-Brometea in our study area: (1) Brometalia erecti (semi-dry grasslands) with Scabioso ochroleucae-Poion angustifoliae (steppe meadows of the forest zone of E Europe) and Cirsio-Brachypodion pinnati (meadow steppes on deep soils in the forest-steppe zone of E Central and E Europe); (2) Festucetalia valesiacae (grass steppes) with Festucion valesiacae (grass steppes on less developed soils in the forest-steppe zone of E Central and E Europe) and Stipion lessingianae (grass steppes in the steppe zone); (3) Stipo-Festucetalia pallentis (rocky steppes) with Asplenio septentrionalis-Festucion pallentis (rocky steppes on siliceous and intermediate soils), Bromo-Festucion pallentis (thermophilous rocky steppes on calcareous soils), Diantho-Seslerion (dealpine Sesleria caerulea grasslands of the Western Carpathians) and Seslerion rigidae (dealpine Sesleria rigida grasslands of the Romanian Carpathians).

Hydrochemical Regions of the Glacial Aquifer System, Northern United States, and Their Environmental and Water-Quality Characteristics

USGS Publications Warehouse

Arnold, Terri L.; Warner, Kelly L.; Groschen, George E.; Caldwell, James P.; Kalkhoff, Stephen J.

2008-01-01

The glacial aquifer system in the United States is a large (953,000 square miles) regional aquifer system of heterogeneous composition. As described in this report, the glacial aquifer system includes all unconsolidated geologic material above bedrock that lies on or north of the line of maximum glacial advance within the United States. Examining ground-water quality on a regional scale indicates that variations in the concentrations of major and minor ions and some trace elements most likely are the result of natural variations in the geologic and physical environment. Study of the glacial aquifer system was designed around a regional framework based on the assumption that two primary characteristics of the aquifer system can affect water quality: intrinsic susceptibility (hydraulic properties) and vulnerability (geochemical properties). The hydrochemical regions described in this report were developed to identify and explain regional spatial variations in ground-water quality in the glacial aquifer system within the hypothetical framework context. Data analyzed for this study were collected from 1991 to 2003 at 1,716 wells open to the glacial aquifer system. Cluster analysis was used to group wells with similar ground-water concentrations of calcium, chloride, fluoride, magnesium, potassium, sodium, sulfate, and bicarbonate into five unique groups. Maximum Likelihood Classification was used to make the extrapolation from clustered groups of wells, defined by points, to areas of similar water quality (hydrochemical regions) defined in a geospatial model. Spatial data that represented average annual precipitation, average annual temperature, land use, land-surface slope, vertical soil permeability, average soil clay content, texture of surficial deposits, type of surficial deposit, and potential for ground-water recharge were used in the Maximum Likelihood Classification to classify the areas so the characteristics of the hydrochemical regions would resemble the characteristics of the clusters. The result of the Maximum Likelihood Classification is a map showing five hydrochemical regions of the glacial aquifer system. Statistical analysis of ion concentrations (calcium, chloride, fluoride, magnesium, sodium, potassium, sulfate, and bicarbonate) in samples collected from wells completed in the glacial aquifer system illustrates that variations in water quality can be explained, in part, by related environmental characteristics that control the movement of ground water through the aquifer system. A comparison of median concentrations of chemical constituents in ground water among the five hydrochemical regions indicates that ground water in the Midwestern Agricultural Region, the Urban-Influenced Region, and the Western Agriculture and Grassland Region has the highest concentrations of major and minor ions, whereas ground water in the Northern and Great Lakes Forested Region and the Mountain and Coastal Forested Region has the lowest concentrations of these ions. Median concentrations of barium, arsenic, lithium, boron, strontium, and nitrite plus nitrate as nitrogen also are significantly different among the hydrochemical regions.

Method for analyzing soil structure according to the size of structural elements

NASA Astrophysics Data System (ADS)

Wieland, Ralf; Rogasik, Helmut

2015-02-01

The soil structure in situ is the result of cropping history and soil development over time. It can be assessed by the size distribution of soil structural elements such as air-filled macro-pores, aggregates and stones, which are responsible for important water and solute transport processes, gas exchange, and the stability of the soil against compacting and shearing forces exerted by agricultural machinery. A method was developed to detect structural elements of the soil in selected horizontal slices of soil core samples with different soil structures in order for them to be implemented accordingly. In the second step, a fitting tool (Eureqa) based on artificial programming was used to find a general function to describe ordered sets of detected structural elements. It was shown that all the samples obey a hyperbolic function: Y(k) = A /(B + k) , k ∈ { 0 , 1 , 2 , … }. This general behavior can be used to develop a classification method based on parameters {A and B}. An open source software program in Python was developed, which can be downloaded together with a selection of soil samples.

Ecological Design of Fernery based on Bioregion Classification System in Ecopark Cibinong Science Center Botanic Gardens, Indonesia

NASA Astrophysics Data System (ADS)

Nafar, S.; Gunawan, A.

2017-10-01

Indonesia as mega biodiversity country has a wide variety of ferns. However, the natural habitats of ferns are currently degrading, particularly in lowlands due to the increasing level of urban-sprawl and industrial zones development. Therefore, Ecology Park (Ecopark) Cibinong Science Center-Botanic Gardens as an ex-situ conservation area is expected to be the best location to conserve the lowland ferns. The purpose of this study is to design a fernery through an ecological landscape design process. The main concept is The Journey of Fern, this concept aiming on providing users experiences in fernery by associating conservational, educational, and recreational aspects. Ecological landscape design as general is applied by the principal of reduce, reuse, and recycle (3R). Bioregion classification system is applied by grouping the plants based on the characteristics of light, water, soil, air, and temperature. The design concept is inspired by the morphology of fern and its growth patterns which is transformed into organic and geometric forms. The result of this study is a design of fernery which consist of welcome area, recreation area, service area, and conservation education area as the main area that providing 66 species of ferns.

Present and potential land use mapping in Mexico

NASA Technical Reports Server (NTRS)

Garduno, H.; Lagos, R. G.; Simo, F. G.

1975-01-01

The Mexican Water Plan (MWP) conducted studies of present and potential land use in Mexico using LANDSAT-1 satellite imagery. Present land use studies were carried out all over the country (197 million hectares); nine soil uses were mapped according to the first classification level recommended by the U.S. Geological Survey. Also 6.3 million hectares of land with advanced erosion were detected. Work was executed at a rate of 8 million hectares per month; reliability was 90% and the cost of only 0.1 cents/hectare. The potential land use study was performed in 45 million hectares at a rate of 4 million hectares per month and at a cost of 0.33 cents/hectare. Soil units according to FAO classification were delineated scale 1:1 million; interpretative maps were also prepared dealing with potential agricultural productivity carrying capacity for cattle, water, erosion risk, and slope ranges.

On soil textural classifications and soil-texture-based estimations

NASA Astrophysics Data System (ADS)

Ángel Martín, Miguel; Pachepsky, Yakov A.; García-Gutiérrez, Carlos; Reyes, Miguel

2018-02-01

The soil texture representation with the standard textural fraction triplet sand-silt-clay is commonly used to estimate soil properties. The objective of this work was to test the hypothesis that other fraction sizes in the triplets may provide a better representation of soil texture for estimating some soil parameters. We estimated the cumulative particle size distribution and bulk density from an entropy-based representation of the textural triplet with experimental data for 6240 soil samples. The results supported the hypothesis. For example, simulated distributions were not significantly different from the original ones in 25 and 85 % of cases when the sand-silt-clay and very coarse+coarse + medium sand - fine + very fine sand - silt+clay were used, respectively. When the same standard and modified triplets were used to estimate the average bulk density, the coefficients of determination were 0.001 and 0.967, respectively. Overall, the textural triplet selection appears to be application and data specific.

Evolution of a soil scientist into an artist: Impacts on my teaching and life

NASA Astrophysics Data System (ADS)

Van Rees, Ken

2017-04-01

Fourteen years ago I began an incredible journey of incorporating art into my soil science field courses. It started out simply with oil pastels and has evolved to students using acrylic paints to interpret the landscapes in addition to the soil classification work that they do on catena sequences around the province. From this foundation, a graduate course was developed where students used soils (and other natural materials) and ground them into pigments to paint different ecosystems; however, the novelty was that students were from both the Soil Science and Master of Fine Arts programs, which created interesting synergies. Throughout this journey, my own art practice began to grow from painting landscapes to developing creative ecological art using burnt trees after a forest fire or capturing imprints of soil profiles with canvas and paint. This presentation will present an overview of my experiences into merging art into my soil science courses and my own life.

On the centennial anniversary of the birth of N.I. Bazilevich: Her contribution to the development of soil science

NASA Astrophysics Data System (ADS)

Pankova, E. I.; Tursina, T. V.; Tishkov, A. A.

2010-11-01

An analysis of the scientific heritage of N.I. Bazilevich is given, and her contribution to the development of soil science in Russia and in the world is appraised. The works of Bazilevich in the field of the genesis of soils concerned the essence of the processes of solodization, takyr formation, solonetzization, salinization, and sodification in the soils of Western Siberia. Many works of Bazilevich were devoted to the geography, cartography, and classification of salt-affected soils. She was an author and an editor of the map of the chemistry of the soil salinization in the Soviet Union. Her investigations into the fields of the biological productivity of ecosystems, biogeochemistry, the biological turnover of elements, and the evolution and dynamics of organic matter and its role in soil formation were of particular significance and brought her international fame. The scientific heritage of Bazilevich is highly acclaimed by modern science. Her students and followers continue to develop her ideas in their works.

Spatial and temporal diversification of crops dynamics in soil erosion modelling. A case study in the arable land of the upper Enziwigger River, Switzerland.

NASA Astrophysics Data System (ADS)

Borrelli, Pasquale; Meusburger, Katrin; Panagos, Panos; Ballabio, Cristiano; Alewell, Christine

2017-04-01

Accelerated soil erosion by water is a widespread phenomenon that affects several Mediterranean and Alpine landscapes causing on-site and off-site environmental impacts. Recognized in the EU Thematic Strategy for Soil Protection as one of the major threats to European soils (COM(2006)231), accelerated soil erosion is a major concern in landscape management and conservation planning (UN SDG 2.4). Agriculture and associated land-use change is the primary cause of accelerated soil erosion. This, because the soil displacement by water erosion mainly occurs when bare-sloped soil surfaces are exposed to the effect of rainfall and overland flow. The Revised Universal Soil Loss Equation (RUSLE) and other RUSLE-based models (which account for more than 90% of current worldwide modelling applications) describe the effect of the vegetation in the so called cover and management factor (C). The C-factor is generally the most challenging modelling component to compute over large study sites. To run a GIS-based RUSLE modelling for a study site greater than few hectares, the use of a simplified approach to assess the C-factor is inevitably necessary. In most of the cases, the C-factor values are assigned to the different land-use classes according to i) the C-values proposed in the literature, and ii) through land-use classifications based on vegetation indices (VI). In previous national (Land Use Policy, 50, 408-421, 2016) and pan-European (Environmental Science & Policy, 54, 438-447, 2015) studies, we computed regional C-values through weighted average operations combining crop statistics with remote sensing and GIS modelling techniques. Here, we present the preliminary results of an object-oriented change detection approach that we are testing to acquire spatial as well temporal crops dynamics at field-scale level in complex agricultural systems.

Spatial modeling of biological soil crusts to support rangeland assessment and monitoring

USGS Publications Warehouse

Bowker, M.A.; Belnap, J.; Miller, M.E.

2006-01-01

Biological soil crusts are a diverse soil surface community, prevalent in semiarid regions, which function as ecosystem engineers and perform numerous important ecosystem services. Loss of crusts has been implicated as a factor leading to accelerated soil erosion and other forms of land degradation. To support assessment and monitoring efforts aimed at ensuring the sustainability of rangeland ecosystems, managers require spatially explicit information concerning potential cover and composition of biological soil crusts. We sampled low disturbance sites in Grand Staircase-Escalante National Monument (Utah, USA) to determine the feasibility of modeling the potential cover and composition of biological soil crusts in a large area. We used classification and regression trees to model cover of four crust types (light cyanobacterial, dark cyanobacterial, moss, lichen) and 1 cyanobacterial biomass proxy (chlorophyll a), based upon a parsimonious set of GIS (Geographic Information Systems) data layers (soil types, precipitation, and elevation). Soil type was consistently the best predictor, although elevation and precipitation were both invoked in the various models. Predicted and observed values for the dark cyanobacterial, moss, and lichen models corresponded moderately well (R 2 = 0.49, 0.64, 0.55, respectively). Cover of late successional crust elements (moss + lichen + dark cyanobacterial) was also successfully modeled (R2 = 0.64). We were less successful with models of light cyanobacterial cover (R2 = 0.22) and chlorophyll a (R2 = 0.09). We believe that our difficulty modeling chlorophyll a concentration is related to a severe drought and subsequent cyanobacterial mortality during the course of the study. These models provide the necessary reference conditions to facilitate the comparison between the actual cover and composition of biological soil crusts at a given site and their potential cover and composition condition so that sites in poor condition can be identified and management actions can be taken.

Synthetic aperture radar for a crop information system: A multipolarization and multitemporal approach

NASA Astrophysics Data System (ADS)

Ban, Yifang

Acquisition of timely information is a critical requirement for successful management of an agricultural monitoring system. Crop identification and crop-area estimation can be done fairly successfully using satellite sensors operating in the visible and near-infrared (VIR) regions of the spectrum. However, data collection can be unreliable due to problems of cloud cover at critical stages of the growing season. The all-weather capability of synthetic aperture radar (SAR) imagery acquired from satellites provides data over large areas whenever crop information is required. At the same time, SAR is sensitive to surface roughness and should be able to provide surface information such as tillage-system characteristics. With the launch of ERS-1, the first long-duration SAR system became available. The analysis of airborne multipolarization SAR data, multitemporal ERS-1 SAR data, and their combinations with VIR data, is necessary for the development of image-analysis methodologies that can be applied to RADARSAT data for extracting agricultural crop information. The overall objective of this research is to evaluate multipolarization airborne SAR data, multitemporal ERS-1 SAR data, and combinations of ERS-1 SAR and satellite VIR data for crop classification using non-conventional algorithms. The study area is situated in Norwich Township, an agricultural area in Oxford County, southern Ontario, Canada. It has been selected as one of the few representative agricultural 'supersites' across Canada at which the relationships between radar data and agriculture are being studied. The major field crops are corn, soybeans, winter wheat, oats, barley, alfalfa, hay, and pasture. Using airborne C-HH and C-HV SAR data, it was found that approaches using contextual information, texture information and per-field classification for improving agricultural crop classification proved to be effective, especially the per-field classification method. Results show that three of the four best per-field classification accuracies (\\ K=0.91) are achieved using combinations of C-HH and C-VV SAR data. This confirms the strong potential of multipolarization data for crop classification. The synergistic effects of multitemporal ERS-1 SAR and Landsat TM data are evaluated for crop classification using an artificial neural network (ANN) approach. The results show that the per-field approach using a feed-forward ANN significantly improves the overall classification accuracy of both single-date and multitemporal SAR data. Using the combination of TM3,4,5 and Aug. 5 SAR data, the best per-field ANN classification of 96.8% was achieved. It represents an 8.5% improvement over a single TM3,4,5 classification alone. Using multitemporal ERS-1 SAR data acquired during the 1992 and 1993 growing seasons, the radar backscatter characteristics of crops and their underlying soils are analyzed. The SAR temporal backscatter profiles were generated for each crop type and the earliest times of the year for differentiation of individual crop types were determined. Orbital (incidence-angle) effects were also observed on all crops. The average difference between the two orbits was about 3 dB. Thus attention should be given to the local incidence-angle effects when using ERS-1 SAR data, especially when comparing fields from different scenes or different areas within the same scene. Finally, early- and mid-season multitemporal SAR data for crop classification using sequential-masking techniques are evaluated, based on the temporal backscatter profiles. It was found that all crops studied could be identified by July 21.

Above the weathering front: contrasting approaches to the study and classification of weathered mantle

NASA Astrophysics Data System (ADS)

Ehlen, Judy

2005-04-01

Weathered mantle comprises the materials above bedrock and below the soil. It can vary in thickness from millimeters to hundreds of meters, depending primarily on climate and parent material. Study of the weathered mantle comes within the realms of four disciplines: geology, geomorphology, soil science, and civil engineering, each of which uses a different approach to describe and classify the material. The approaches of engineers, geomorphologists, and geologists are contrasted and compared using example papers from the published literature. Soil scientists rarely study the weathering profile as such, and instead concentrate upon soil-forming processes and spatial distribution primarily in the solum. Engineers, including engineering geologists, study the stability and durability of the weathered mantle and the strength of the materials using sophisticated procedures to classify weathered materials, but their approach tends to be one-dimensional. Furthermore, they believe that the study of mineralogy and chemistry is not useful. Geomorphologists deal with weathering in terms of process—how the weathered mantle is formed—and with respect to landform evolution using a spatial approach. Geologists tend to ignore the weathered mantle because it is not bedrock, or to study its mineralogy and/or chemistry in the laboratory. I recommend that the approaches of the various disciplines be integrated—geomorphologists and geologists should consider using engineering weathering classifications, and geologists should adopt a spatial perspective to weathering, as should engineers and engineering geologists.

The impact on the soil microbial community and enzyme activity of two earthworm species during the bioremediation of pentachlorophenol-contaminated soils.

PubMed

Lin, Zhong; Zhen, Zhen; Wu, Zhihao; Yang, Jiewen; Zhong, Laiyuan; Hu, Hanqiao; Luo, Chunling; Bai, Jing; Li, Yongtao; Zhang, Dayi

2016-01-15

The ecological effect of earthworms on the fate of soil pentachlorophenol (PCP) differs with species. This study addressed the roles and mechanisms by which two earthworm species (epigeic Eisenia fetida and endogeic Amynthas robustus E. Perrier) affect the soil microbial community and enzyme activity during the bioremediation of PCP-contaminated soils. A. robustus removed more soil PCP than did E. foetida. A. robustus improved nitrogen utilisation efficiency and soil oxidation more than did E. foetida, whereas the latter promoted the organic matter cycle in the soil. Both earthworm species significantly increased the amount of cultivable bacteria and actinomyces in soils, enhancing the utilisation rate of the carbon source (i.e. carbohydrates, carboxyl acids, and amino acids) and improving the richness and evenness of the soil microbial community. Additionally, earthworm treatment optimized the soil microbial community and increased the amount of the PCP-4-monooxygenase gene. Phylogenic classification revealed stimulation of indigenous PCP bacterial degraders, as assigned to the families Flavobacteriaceae, Pseudomonadaceae and Sphingobacteriacea, by both earthworms. A. robustus and E. foetida specifically promoted Comamonadaceae and Moraxellaceae PCP degraders, respectively. Copyright © 2015 Elsevier B.V. All rights reserved.

Object-Based Classification and Change Detection of Hokkaido, Japan

NASA Astrophysics Data System (ADS)

Park, J. G.; Harada, I.; Kwak, Y.

2016-06-01

Topography and geology are factors to characterize the distribution of natural vegetation. Topographic contour is particularly influential on the living conditions of plants such as soil moisture, sunlight, and windiness. Vegetation associations having similar characteristics are present in locations having similar topographic conditions unless natural disturbances such as landslides and forest fires or artificial disturbances such as deforestation and man-made plantation bring about changes in such conditions. We developed a vegetation map of Japan using an object-based segmentation approach with topographic information (elevation, slope, slope direction) that is closely related to the distribution of vegetation. The results found that the object-based classification is more effective to produce a vegetation map than the pixel-based classification.

Using remote sensing and GIS techniques to estimate discharge and recharge fluxes for the Death Valley regional groundwater flow system, USA

USGS Publications Warehouse

D'Agnese, F. A.; Faunt, C.C.; Turner, A.K.; ,

1996-01-01

The recharge and discharge components of the Death Valley regional groundwater flow system were defined by techniques that integrated disparate data types to develop a spatially complex representation of near-surface hydrological processes. Image classification methods were applied to multispectral satellite data to produce a vegetation map. The vegetation map was combined with ancillary data in a GIS to delineate different types of wetlands, phreatophytes and wet playa areas. Existing evapotranspiration-rate estimates were used to calculate discharge volumes for these area. An empirical method of groundwater recharge estimation was modified to incorporate data describing soil-moisture conditions, and a recharge potential map was produced. These discharge and recharge maps were readily converted to data arrays for numerical modelling codes. Inverse parameter estimation techniques also used these data to evaluate the reliability and sensitivity of estimated values.The recharge and discharge components of the Death Valley regional groundwater flow system were defined by remote sensing and GIS techniques that integrated disparate data types to develop a spatially complex representation of near-surface hydrological processes. Image classification methods were applied to multispectral satellite data to produce a vegetation map. This map provided a basis for subsequent evapotranspiration and infiltration estimations. The vegetation map was combined with ancillary data in a GIS to delineate different types of wetlands, phreatophytes and wet playa areas. Existing evapotranspiration-rate estimates were then used to calculate discharge volumes for these areas. A previously used empirical method of groundwater recharge estimation was modified by GIS methods to incorporate data describing soil-moisture conditions, and a recharge potential map was produced. These discharge and recharge maps were readily converted to data arrays for numerical modelling codes. Inverse parameter estimation techniques also used these data to evaluate the reliability and sensitivity of estimated values.

Evaluation of areas prepared for planting using LANDSAT data. M.S. Thesis; [Ribeirao Preto, Brazil

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Deassuncao, G. V.; Duarte, V.

1983-01-01

Three different algorithms (SINGLE-CELL, MAXVER and MEDIA K) were used to automatically interpret data from LANDSAT observations of an area of Ribeirao Preto, Brazil. Photographic transparencies were obtained, projected and visually interpreted. The results show that: (1) the MAXVER algorithm presented a better classification performance; (2) verification of the changes in cultivated areas using data from the three different acquisition dates was possible; (3) the water bodies, degraded lands, urban areas, and fallow fields were frequently mistaken by cultivated soils; and (4) the use of projected photographic transparencies furnished satisfactory results, besides reducing the time spent on the image-100 system.

Slopeland utilizable limitation classification using landslide inventory

NASA Astrophysics Data System (ADS)

Tsai, Shu Fen; Lin, Chao Yuan

2016-04-01

In 1976, "Slopeland Conservation and Utilization Act" was promulgated as well as the criteria for slopeland utilization limitation classification (SULC) i.e., average slope, effective soil depth, degree of soil erosion, and parent rock became standardized. Due to the development areas on slope land steadily increased and the extreme rainfall events occurred frequently, the areas affected by landslides also increased year by year. According to the act, the land which damaged by disaster must be categorized to the conservation land and required rehabilitation. Nevertheless, the large-scale disaster on slope land and the limitation of SWCB officers are the constraint of field investigation. Therefore, how to establish the ongoing inspective procedure of post-disaster SULC using remote sensing was essential. A-Li-Shan, Ai-Liao, and Tai-Ma-Li Watershed were selected to be case studies in this project. The spatial data from big data i.e., Digital Elevation Model (DEM), soil map, and satellite images integrated with Geographic Information Systems (GIS) were applied to post-disaster SULC. The collapse and deposition area which delineated by vegetation recovery rate was established landslide inventory of cadastral unit combined with watershed unit. The results were verified with field survey and the accuracy was 97%. The landslide inventory could be an effective reference for sediment disaster investigation and a practical evidence for judgement to expropriation. Finally, the results showed that the ongoing inspective procedure of post-disaster SULC was practicable. From the four criteria, the average slope was the major factor. It was found that the non-uniform slopes, especially derived from cadastral units, often produce significant slope difference and lead to errors of average slope evaluation. Therefore, the Grid-based DEM slope derivation has been recommended as the standard method to calculate the average slope. Others criteria were previously required to classify the farm land tax. However, as a result of environmental change and advancements in farm machinery, it seems that those criteria were further inappropriate criteria for agricultural land. In conclusion, soil and water conservation works, which were enhanced to disaster prevention under climate change, should reconsider the SULC criteria. The average slope from DEM derivation and the sediment disaster from landslide inventory were suggested and adequate for SULC.

Integrating Blue Carbon Initiatives with the Management of Wildlife Cobenefits: a Case Study at the Nisqually River Delta, WA

NASA Astrophysics Data System (ADS)

Woo, I.; De La Cruz, S.; Windham-Myers, L.; Thorne, K.; Drexler, J. Z.; Byrd, K. B.; Bergamaschi, B. A.; Davis, M.; Anderson, F. E.; Ballanti, L.; Zhu, Z.; Schmerfeld, J.; Johnson, K.; Nakai, G.

2016-12-01

Carbon transport, cycling, and storage within coastal wetlands are amongst the most fundamental processes that support estuarine ecosystem services. In addition to providing habitat and trophic support for wildlife populations and fisheries, coastal wetlands accumulate and store carbon at significant rates. By capturing and storing carbon in soils, coastal wetland can play a vital role in offsetting greenhouse gasses, thereby helping mitigate the impacts of climate change. Estuarine restoration has significant potential to simultaneously increase carbon sequestration and ecosystem functioning for wildlife, linking traditional objectives of protecting, restoring, and managing diverse wetlands to support a broad array of species and their habitats with carbon sequestration initiatives. The Nisqually River Delta is the largest wetland restoration in the Pacific Northwest and is an ideal site to document the carbon co-benefits of a restoring and natural marsh. We compared the sources of carbon that enter food webs to carbon that has accumulated in soils. Juvenile Chinook foodwebs incorporated freshwater/brackish as well as estuarine-derived carbon sources. Soil carbon inputs reflected relatively recent estuarine restoration and a century of diked agricultural and fallow field land use history. A Net Ecosystem Carbon Balance will use EC flux towers to quantify CO2 and CH4 atmospheric flux and constrain aqueous dissolved carbon flux in channels. Ultimately, we will assess the resiliency of tidal marsh under past, present, and future sediment delivery scenarios. Past and present sedimentation data will be analyzed from our soil cores. Future scenarios incorporating potential management strategies to increase sediment delivery onto the delta will be leveraged with existing studies of hydrodynamics and sedimentation models. These scenarios will be used as model inputs to assess the viability of marshes as a result of prospective management strategies and sea-level rise. Historical and current imagery using a hierarchical classification framework and object based image classification system will be used to assess habitat change. Future habitat potential will be mapped based on management scenarios, hydrodynamic/sedimentation model outputs, and marsh resiliency model outputs.

Identifying riparian sinks for watershed nitrate using soil surveys.

PubMed

Rosenblatt, A E; Gold, A J; Stolt, M H; Groffman, P M; Kellogg, D Q

2001-01-01

The capacity of riparian zones to serve as critical control locations for watershed nitrogen flux varies with site characteristics. Without a means to stratify riparian zones into different levels of ground water nitrate removal capacity, this variability will confound spatially explicit source-sink models of watershed nitrate flux and limit efforts to target riparian restoration and management. We examined the capability of SSURGO (1:15 840 Soil Survey Geographic database) map classifications (slope class, geomorphology, and/or hydric soil designation) to identify riparian sites with high capacity for ground water nitrate removal. The study focused on 100 randomly selected riparian locations in a variety of forested and glaciated settings within Rhode Island. Geomorphic settings included till, outwash, and organic/alluvial deposits. We defined riparian zones with "high ground water nitrate removal capacity" as field sites possessing both >10 m of hydric soil width and an absence of ground water surface seeps. SSURGO classification based on a combination of geomorphology and hydric soil status created two functionally distinct sets of riparian sites. More than 75% of riparian sites classified by SSURGO as organic/alluviumhydric or as outwash-hydric had field attributes that suggest a high capacity for ground water nitrate removal. In contrast, >85% of all till sites and nonhydric outwash sites had field characteristics that minimize the capacity for ground water nitrate removal. Comparing the STATSGO and SSURGO databases for a 64000-ha watershed, STATSGO grossly under-represented critical riparian features. We conclude that the SSURGO database can provide modelers and managers with important insights into riparian zone nitrogen removal potential.

Delineation of colluvial soils in different soil regions

NASA Astrophysics Data System (ADS)

Zádorová, Tereza; Penížek, Vít; Vašát, Radim

2015-04-01

Colluvial soils are considered to be the direct result of accelerated soil erosion in agricultural landscape, resulting in accumulation of humus-rich soil material in terrain depressions and toe slopes. They represent an important soil cover element in landscapes influenced by soil erosion and form an important soil organic carbon (SOC) pool. Delineation of colluvial soils can identify areas with high sediment input and potential deep organic carbon storage and thus improve our knowledge on soil mass and SOC stock redistribution in dissected landscapes. Different prediction methods (ordinary kriging, multiple linear regression, supervised fuzzy classification, artificial neural network, support vector machines) for colluvial soils delineation have been tested in three different soil regions (Cambisol, Luvisol and Chernozem) at two scales (plot and watershed) in the Czech Republic. The approach is based on exploitation of relationship between soil and terrain units and assumes that colluvial soil can be defined by particular range of terrain attributes values. Terrain attributes derived from precise DEMs were used as predictors in applied models. The soil-terrain relationship was assessed using a large dataset of field investigations (300 cores at each plot and 100 cores at each watershed). Models were trained at plot scale (15-33 ha) and the best performing model was then calibrated and validated at watershed scale (25-55 km2). The study proved high potential of terrain variables as predictors in colluvial soil delineation. Support vector machines method was the best performing method for colluvial soil occurrence prediction at all the three sites. However, significant differences in performance have been identified among the studied plots. The best results were obtained in Luvisol region where both determination coefficient and prediction accuracy reached the highest values. The model performance was satisfactory also in Chernozem region. The model showed its limitations in the Cambisol region, where a high uncertainty and low prediction accuracy resulted from generally weak soil-terrain relationship given by low redistribution of the soil material. Different terrain attributes were applied as predictors in the models at each study region. In the Chernozem region, the colluvial area is defined by extreme values of slope and topographic position index. In Luvisol and Cambisol regions, colluvial soil area is related mostly to specific values of plan curvature and topographic wetness index. Role of colluvial soils given by theirs spatial extent differs in the studied sites. Colluvial soil in the Chernozem region represents an important soil cover part (13% from the total area). Moderate importance of colluvial soils was determined in the Luvisol region (8 %) and low in the Cambisol region (3%). Spatial extent of colluvial soils corresponds to the intensity of soil mass redistribution. At the three sites with similar environmental settings (terrain, land management, climate), it is mostly soil characteristics and profile development typical for each classification unit that resulted in different importance of colluvial soil in each study site. The study was supported by grant nr. 13-07516P of the Czech science foundation and by grant nr. QJ1230319 of the Ministry of Agriculture.

Completing the land resource hierarchy

USDA-ARS?s Scientific Manuscript database

The Land Resource Hierarchy of the NRCS is a hierarchal landscape classification consisting of resource areas which represent both conceptual and spatially discrete landscape units stratifying agency programs and practices. The Land Resource Hierarchy (LRH) scales from discrete points (soil pedon an...

Creating a Canonical Scientific and Technical Information Classification System for NCSTRL+

NASA Technical Reports Server (NTRS)

Tiffany, Melissa E.; Nelson, Michael L.

1998-01-01

The purpose of this paper is to describe the new subject classification system for the NCSTRL+ project. NCSTRL+ is a canonical digital library (DL) based on the Networked Computer Science Technical Report Library (NCSTRL). The current NCSTRL+ classification system uses the NASA Scientific and Technical (STI) subject classifications, which has a bias towards the aerospace, aeronautics, and engineering disciplines. Examination of other scientific and technical information classification systems showed similar discipline-centric weaknesses. Traditional, library-oriented classification systems represented all disciplines, but were too generalized to serve the needs of a scientific and technically oriented digital library. Lack of a suitable existing classification system led to the creation of a lightweight, balanced, general classification system that allows the mapping of more specialized classification schemes into the new framework. We have developed the following classification system to give equal weight to all STI disciplines, while being compact and lightweight.

ENGINEERING-GEOLOGY SITE APPRAISAL OF THE FEDERAL CAPITAL TERRITORY, NIGERIA.

USGS Publications Warehouse

Ege, J.R.; Griffitts, W.R.; Overstreet, W.C.

1985-01-01

The 7,700-km**2-area Federal Capital Territory, Nigeria, is underlain by crystalline igneous and metamorphic rocks of Precambrian age. Laterite caps many hills of Cretaceous rock, some hills of Precambrian rock, and crops out near stream banks in the east and northeast. The most conspicuous structural features are a broad 'J'-shaped fold traversing the eastern and central part of the Territory and a north-trending shear zone along the eastern boundary. The soils of the Territory are lateritic and belong to the SW-SP-SM (Unified Soil Classification System) groups covering Precambrian migmatites, gneisses and granites and the SC group covering Cretaceous sediments and Precambrian mica-rich schists. The engineering characteristics of the rocks are medium- to high-strength massive and gneissic rock, low-to medium-strength bedded rock, and low-strength foliated and sheared rock. An area of at least 800 km**2 is free from apparent geological hazards and should be suitable for construction of a capital city, its environs and supporting facilities.

Detection of terrain indices related to soil salinity and mapping salt-affected soils using remote sensing and geostatistical techniques.

PubMed

Triki Fourati, Hela; Bouaziz, Moncef; Benzina, Mourad; Bouaziz, Samir

2017-04-01

Traditional surveying methods of soil properties over landscapes are dramatically cost and time-consuming. Thus, remote sensing is a proper choice for monitoring environmental problem. This research aims to study the effect of environmental factors on soil salinity and to map the spatial distribution of this salinity over the southern east part of Tunisia by means of remote sensing and geostatistical techniques. For this purpose, we used Advanced Spaceborne Thermal Emission and Reflection Radiometer data to depict geomorphological parameters: elevation, slope, plan curvature (PLC), profile curvature (PRC), and aspect. Pearson correlation between these parameters and soil electrical conductivity (EC soil ) showed that mainly slope and elevation affect the concentration of salt in soil. Moreover, spectral analysis illustrated the high potential of short-wave infrared (SWIR) bands to identify saline soils. To map soil salinity in southern Tunisia, ordinary kriging (OK), minimum distance (MD) classification, and simple regression (SR) were used. The findings showed that ordinary kriging technique provides the most reliable performances to identify and classify saline soils over the study area with a root mean square error of 1.83 and mean error of 0.018.

Spatial variability and its main controlling factors of the permafrost soil-moisture on the northern-slope of Bayan Har Mountains in Qinghai-Tibet Plateau

NASA Astrophysics Data System (ADS)

Cao, W.; Sheng, Y.

2017-12-01

The soil moisture movement is an important carrier of material cycle and energy flow among the various geo-spheres in the cold regions. It is very critical to protect the alpine ecology and hydrologic cycle in Qinghai-Tibet Plateau. Especially, it becomes one of the key problems to reveal the spatial-temporal variability of soil moisture movement and its main influence factors in earth system science. Thus, this research takes the north slope of Bayan Har Mountains in Qinghai-Tibet Plateau as a case study. The present study firstly investigates the change of permafrost moisture in different slope positions and depths. Based on this investigation, this article attempts to investigate the spatial variability of permafrost moisture and identifies the key influence factors in different terrain conditions. The method of classification and regression tree (CART) is adopted to identify the main controlling factors influencing the soil moisture movement. And the relationships between soil moisture and environmental factors are revealed by the use of the method of canonical correspondence analysis (CCA). The results show that: 1) the change of the soil moisture on the permafrost slope is divided into 4 stages, including the freezing stability phase, the rapid thawing phase, the thawing stability phase and the fast freezing phase; 2) this greatly enhances the horizontal flow in the freezing period due to the terrain slope and the freezing-thawing process. Vertical migration is the mainly form of the soil moisture movement. It leads to that the soil-moisture content in the up-slope is higher than that in the down-slope. On the contrary, the soil-moisture content in the up-slope is lower than that in the down-slope during the melting period; 3) the main environmental factors which affect the slope-permafrost soil-moisture are elevation, soil texture, soil temperature and vegetation coverage. But there are differences in the impact factors of the soil moisture in different freezing-thawing stages; 4) the main factors that affect the slope-permafrost soil-moisture at the shallow depth of 0-20cm are slope, elevation and vegetation coverage. And the main factors influencing the soil moisture at the middle and lower depth are complex.

Identification of a dynamic temperature threshold for soil moisture freeze/thaw (F/T) state classification using soil real dielectric constant derivatives.

NASA Astrophysics Data System (ADS)

Pardo, R.; Berg, A. A.; Warland, J. S.

2017-12-01

The use of microwave remote sensing for surface ground ice detection has been well documented using both active and passive systems. Typical validation of these remotely sensed F/T state products relies on in-situ air or soil temperature measurements and a threshold of 0°C to identify frozen soil. However, in soil pores, the effects of capillary and adsorptive forces combine with the presence of dissolved salts to depress the freezing point. This is further confounded by the fact that water over this temperature range releases/absorbs latent heat of freezing/fusion. Indeed, recent results from SLAPEx2015, a campaign conducted to evaluate the ability to detect F/T state and examine the controls on F/T detection at multiple resolutions, suggest that using a soil temperature of 0°C as a threshold for freezing may not be appropriate. Coaxial impedance sensors, like Steven's HydraProbeII (HP), are the most widely used soil sensor in water supply forecast and climatological networks. These soil moisture probes have recently been used to validate remote sensing F/T products. This kind of validation is still relatively uncommon and dependent on categorical techniques based on seasonal reference states of frozen and non-frozen soil conditions. An experiment was conducted to identify the correlation between the phase state of the soil moisture and the probe measurements. Eight soil cores were subjected to F/T transitions in an environmental chamber. For each core, at a depth of 2.5 cm, the temperature and real dielectric constant (rdc) were measured every five minutes using HPs while two heat pulse probes captured the apparent heat capacity 24 minutes apart. Preliminary results show the phase transition of water is bounded by inflection points in the soil temperature, attributed to latent heat. The rdc, however, appears to be highly sensitive to changes in the water preceding the phase change. This opens the possibility of estimating a dynamic temperature threshold for soil F/T by identifying the soil temperatures at the times during which these inflection points in the soil rdc occur. This technique provides a more accurate threshold for F/T product than the static reference temperature currently established.

Spectral feature design in high dimensional multispectral data

NASA Technical Reports Server (NTRS)

Chen, Chih-Chien Thomas; Landgrebe, David A.

1988-01-01

The High resolution Imaging Spectrometer (HIRIS) is designed to acquire images simultaneously in 192 spectral bands in the 0.4 to 2.5 micrometers wavelength region. It will make possible the collection of essentially continuous reflectance spectra at a spectral resolution sufficient to extract significantly enhanced amounts of information from return signals as compared to existing systems. The advantages of such high dimensional data come at a cost of increased system and data complexity. For example, since the finer the spectral resolution, the higher the data rate, it becomes impractical to design the sensor to be operated continuously. It is essential to find new ways to preprocess the data which reduce the data rate while at the same time maintaining the information content of the high dimensional signal produced. Four spectral feature design techniques are developed from the Weighted Karhunen-Loeve Transforms: (1) non-overlapping band feature selection algorithm; (2) overlapping band feature selection algorithm; (3) Walsh function approach; and (4) infinite clipped optimal function approach. The infinite clipped optimal function approach is chosen since the features are easiest to find and their classification performance is the best. After the preprocessed data has been received at the ground station, canonical analysis is further used to find the best set of features under the criterion that maximal class separability is achieved. Both 100 dimensional vegetation data and 200 dimensional soil data were used to test the spectral feature design system. It was shown that the infinite clipped versions of the first 16 optimal features had excellent classification performance. The overall probability of correct classification is over 90 percent while providing for a reduced downlink data rate by a factor of 10.

A Nodal Domain Integration Model of Two-Dimensional Heat and Soil-Water Flow Coupled by Soil-Water Phase Change.

DTIC Science & Technology

1987-06-01

WORK UNIT ELEMENT NO. NO NO ACCESSION NO I I ICWIS 31711 11 TITLE (Include Security Classification) A Nodal Domain Integration Model of Two...t.5% Unclassified."- .-,,. PREFACE This report was prepared by Ted Hromadka, Director of Water Re- sources, Williamson and Schmid. The work was...performed for CRREL under Contract 84-M-1691 and was funded by the Directorate of Civil Works , Office of the Chief of Engineers, under Civil Works Order No

A Comparative Assessment of the Influences of Human Impacts on Soil Cd Concentrations Based on Stepwise Linear Regression, Classification and Regression Tree, and Random Forest Models

PubMed Central

Qiu, Lefeng; Wang, Kai; Long, Wenli; Wang, Ke; Hu, Wei; Amable, Gabriel S.

2016-01-01

Soil cadmium (Cd) contamination has attracted a great deal of attention because of its detrimental effects on animals and humans. This study aimed to develop and compare the performances of stepwise linear regression (SLR), classification and regression tree (CART) and random forest (RF) models in the prediction and mapping of the spatial distribution of soil Cd and to identify likely sources of Cd accumulation in Fuyang County, eastern China. Soil Cd data from 276 topsoil (0–20 cm) samples were collected and randomly divided into calibration (222 samples) and validation datasets (54 samples). Auxiliary data, including detailed land use information, soil organic matter, soil pH, and topographic data, were incorporated into the models to simulate the soil Cd concentrations and further identify the main factors influencing soil Cd variation. The predictive models for soil Cd concentration exhibited acceptable overall accuracies (72.22% for SLR, 70.37% for CART, and 75.93% for RF). The SLR model exhibited the largest predicted deviation, with a mean error (ME) of 0.074 mg/kg, a mean absolute error (MAE) of 0.160 mg/kg, and a root mean squared error (RMSE) of 0.274 mg/kg, and the RF model produced the results closest to the observed values, with an ME of 0.002 mg/kg, an MAE of 0.132 mg/kg, and an RMSE of 0.198 mg/kg. The RF model also exhibited the greatest R2 value (0.772). The CART model predictions closely followed, with ME, MAE, RMSE, and R2 values of 0.013 mg/kg, 0.154 mg/kg, 0.230 mg/kg and 0.644, respectively. The three prediction maps generally exhibited similar and realistic spatial patterns of soil Cd contamination. The heavily Cd-affected areas were primarily located in the alluvial valley plain of the Fuchun River and its tributaries because of the dramatic industrialization and urbanization processes that have occurred there. The most important variable for explaining high levels of soil Cd accumulation was the presence of metal smelting industries. The good performance of the RF model was attributable to its ability to handle the non-linear and hierarchical relationships between soil Cd and environmental variables. These results confirm that the RF approach is promising for the prediction and spatial distribution mapping of soil Cd at the regional scale. PMID:26964095

Assessing the spatial distribution of glyphosate-AMPA in an Argentinian farm field using a pedometric technique

NASA Astrophysics Data System (ADS)

Barbera, Agustin; Zamora, Martin; Domenech, Marisa; Vega-Becerra, Andres; Castro-Franco, Mauricio

2017-04-01

The cultivation of transgenic glyphosate-resistant crops has been the most rapidly adopted crop technology in Argentina since 1997. Thus, more than 180 million liters of the broad-spectrum herbicide glyphosate (N - phosphonomethylglicine) are applied every year. The intensive use of glyphosate combined with geomorphometrical characteristics of the Pampa region is a matter of environmental concern. An integral component of assessing the risk of soil contamination in farm fields is to describe the spatial distribution of the levels of contaminant agent. Application of pedometric techniques for this purpose has been scarcely demonstrated. These techniques could provide an estimate of the concentration at a given unsampled location, as well as the probability that concentration will exceed the critical threshold concentration. In this work, a pedometric technique for assessing the spatial distribution of glyphosate in farm fields was developed. A field located at INTA Barrow, Argentina (Lat: -38.322844, Lon: -60.25572) which has a great soil spatial variability, was divided by soil-specific zones using a pedometric technique. This was developed integrating INTA Soil Survey information and a digital elevation model (DEM) obtained from a DGPS. Firstly, 10 topographic indices derived from a DEM were computed in a Random Forest algorithm to obtain a classification model for soil map units (SMU). Secondly, a classification model was applied to those topographic indices but at a scale higher than 1:1000. Finally, a spatial principal component analysis and a clustering using Fuzzy K-means were used into each SMU. From this clustering, three soil-specific zones were determined which were also validated through apparent electrical conductivity (CEa) measurements. Three soil sample points were determined by zone. In each one, samples from 0-10, 10-20 and 20-40cm depth were taken. Glyphosate content and AMPA in each soil sample were analyzed using de UPLC-MS/MS ESI (+/-). Only AMPA at 10-20 cm depth had significant difference among soil-specific zones. However, marked trends for glyphosate content and AMPA were clearly shown among zones. These results suggest that (i) the presence of glyphosate and AMPA has spatial patterns distribution related to soil properties at field scale; and (ii) the proposed technique allowed to determine soil-specific zones related to the spatial distribution of glyphosate and AMPA fast, cost-effective and accurately. In further works, we would suggest adding new soil information sources to improve soil-specific zone delimitation.

A Comparative Assessment of the Influences of Human Impacts on Soil Cd Concentrations Based on Stepwise Linear Regression, Classification and Regression Tree, and Random Forest Models.

PubMed

Qiu, Lefeng; Wang, Kai; Long, Wenli; Wang, Ke; Hu, Wei; Amable, Gabriel S

2016-01-01

Soil cadmium (Cd) contamination has attracted a great deal of attention because of its detrimental effects on animals and humans. This study aimed to develop and compare the performances of stepwise linear regression (SLR), classification and regression tree (CART) and random forest (RF) models in the prediction and mapping of the spatial distribution of soil Cd and to identify likely sources of Cd accumulation in Fuyang County, eastern China. Soil Cd data from 276 topsoil (0-20 cm) samples were collected and randomly divided into calibration (222 samples) and validation datasets (54 samples). Auxiliary data, including detailed land use information, soil organic matter, soil pH, and topographic data, were incorporated into the models to simulate the soil Cd concentrations and further identify the main factors influencing soil Cd variation. The predictive models for soil Cd concentration exhibited acceptable overall accuracies (72.22% for SLR, 70.37% for CART, and 75.93% for RF). The SLR model exhibited the largest predicted deviation, with a mean error (ME) of 0.074 mg/kg, a mean absolute error (MAE) of 0.160 mg/kg, and a root mean squared error (RMSE) of 0.274 mg/kg, and the RF model produced the results closest to the observed values, with an ME of 0.002 mg/kg, an MAE of 0.132 mg/kg, and an RMSE of 0.198 mg/kg. The RF model also exhibited the greatest R2 value (0.772). The CART model predictions closely followed, with ME, MAE, RMSE, and R2 values of 0.013 mg/kg, 0.154 mg/kg, 0.230 mg/kg and 0.644, respectively. The three prediction maps generally exhibited similar and realistic spatial patterns of soil Cd contamination. The heavily Cd-affected areas were primarily located in the alluvial valley plain of the Fuchun River and its tributaries because of the dramatic industrialization and urbanization processes that have occurred there. The most important variable for explaining high levels of soil Cd accumulation was the presence of metal smelting industries. The good performance of the RF model was attributable to its ability to handle the non-linear and hierarchical relationships between soil Cd and environmental variables. These results confirm that the RF approach is promising for the prediction and spatial distribution mapping of soil Cd at the regional scale.

Using LUCAS topsoil database to estimate soil organic carbon content in local spectral libraries

NASA Astrophysics Data System (ADS)

Castaldi, Fabio; van Wesemael, Bas; Chabrillat, Sabine; Chartin, Caroline

2017-04-01

The quantification of the soil organic carbon (SOC) content over large areas is mandatory to obtain accurate soil characterization and classification, which can improve site specific management at local or regional scale exploiting the strong relationship between SOC and crop growth. The estimation of the SOC is not only important for agricultural purposes: in recent years, the increasing attention towards global warming highlighted the crucial role of the soil in the global carbon cycle. In this context, soil spectroscopy is a well consolidated and widespread method to estimate soil variables exploiting the interaction between chromophores and electromagnetic radiation. The importance of spectroscopy in soil science is reflected by the increasing number of large soil spectral libraries collected in the world. These large libraries contain soil samples derived from a consistent number of pedological regions and thus from different parent material and soil types; this heterogeneity entails, in turn, a large variability in terms of mineralogical and organic composition. In the light of the huge variability of the spectral responses to SOC content and composition, a rigorous classification process is necessary to subset large spectral libraries and to avoid the calibration of global models failing to predict local variation in SOC content. In this regard, this study proposes a method to subset the European LUCAS topsoil database into soil classes using a clustering analysis based on a large number of soil properties. The LUCAS database was chosen to apply a standardized multivariate calibration approach valid for large areas without the need for extensive field and laboratory work for calibration of local models. Seven soil classes were detected by the clustering analyses and the samples belonging to each class were used to calibrate specific partial least square regression (PLSR) models to estimate SOC content of three local libraries collected in Belgium (Loam belt and Wallonia) and Luxembourg. The three local libraries only consist of spectral data (199 samples) acquired using the same protocol as the one used for the LUCAS database. SOC was estimated with a good accuracy both within each local library (RMSE: 1.2 ÷ 5.4 g kg-1; RPD: 1.41 ÷ 2.06) and for the samples of the three libraries together (RMSE: 3.9 g kg-1; RPD: 2.47). The proposed approach could allow to estimate SOC everywhere in Europe only collecting spectra, without the need for chemical laboratory analyses, exploiting the potentiality of the LUCAS database and specific PLSR models.

A web-based land cover classification system based on ontology model of different classification systems

NASA Astrophysics Data System (ADS)

Lin, Y.; Chen, X.

2016-12-01

Land cover classification systems used in remote sensing image data have been developed to meet the needs for depicting land covers in scientific investigations and policy decisions. However, accuracy assessments of a spate of data sets demonstrate that compared with the real physiognomy, each of the thematic map of specific land cover classification system contains some unavoidable flaws and unintended deviation. This work proposes a web-based land cover classification system, an integrated prototype, based on an ontology model of various classification systems, each of which is assigned the same weight in the final determination of land cover type. Ontology, a formal explication of specific concepts and relations, is employed in this prototype to build up the connections among different systems to resolve the naming conflicts. The process is initialized by measuring semantic similarity between terminologies in the systems and the search key to produce certain set of satisfied classifications, and carries on through searching the predefined relations in concepts of all classification systems to generate classification maps with user-specified land cover type highlighted, based on probability calculated by votes from data sets with different classification system adopted. The present system is verified and validated by comparing the classification results with those most common systems. Due to full consideration and meaningful expression of each classification system using ontology and the convenience that the web brings with itself, this system, as a preliminary model, proposes a flexible and extensible architecture for classification system integration and data fusion, thereby providing a strong foundation for the future work.

Vegetation and Soils

Treesearch

Sammy L. King; Mark H. Eisenbies; David Gartner

2000-01-01

Characterization of bottomland hardwood vegetation in relatively undisturbed forests can provide critical information for developing effective wetland creation and restoration techniques and for assessing the impacts of management and development. Classification is a useful technique in characterizing vegetation because it summarizes complex data sets, assists in...

Site suitability for riverbed filtration system in Tanah Merah, Kelantan-A physical model study for turbidity removal

NASA Astrophysics Data System (ADS)

Ghani, Mastura; Adlan, Mohd Nordin; Kamal, Nurul Hana Mokhtar; Aziz, Hamidi Abdul

2017-10-01

A laboratory physical model study on riverbed filtration (RBeF) was conducted to investigate site suitability of soil from Tanah Merah, Kelantan for RBeF. Soil samples were collected and transported to the Geotechnical Engineering Laboratory, Universiti Sains Malaysia for sieve analysis and hydraulic conductivity tests. A physical model was fabricated with gravel packs laid at the bottom of it to cover the screen and then soil sample were placed above gravel pack for 30 cm depth. River water samples from Lubok Buntar, Kedah were used to simulate the effectiveness of RBeF for turbidity removal. Turbidity readings were tested at the inlet and outlet of the filter with specified flow rate. Results from soil characterization show that the soil samples were classified as poorly graded sand with hydraulic conductivity ranged from 7.95 x 10-3 to 6.61 x 10-2 cm/s. Turbidity removal ranged from 44.91% - 92.75% based on the turbidity of water samples before filtration in the range of 33.1-161 NTU. The turbidity of water samples after RBeF could be enhanced up to 2.53 NTU. River water samples with higher turbidity of more than 160 NTU could only reach 50% or less removal by the physical model. Flow rates of the RBeF were in the range of 0.11-1.61 L/min while flow rates at the inlet were set up between 2-4 L/min. Based on the result of soil classification, Tanah Merah site is suitable for RBeF whereas result from physical model study suggested that 30 cm depth of filter media is not sufficient to be used if river water turbidity is higher.

Application of remote sensing technology to land evaluation, planning utilization of land resources, and assessment of wildlife areas in eastern South Dakota

NASA Technical Reports Server (NTRS)

1975-01-01

A soils map for land evaluation in Potter County (Eastern South Dakota) was developed to demonstrate the use of remote sensing technology in the area of diverse parent materials and topography. General land use and soils maps have also been developed for land planning LANDSAT, RB-57 imagery, and USGS photographs are being evaluated for making soils and land use maps. LANDSAT fulfilled the requirements for general land use and a general soils map. RB-57 imagery supplemented by large scale black and white stereo coverage was required to provide the detail needed for the final soils map for land evaluation. Color infrared prints excelled black and white coverage for this soil mapping effort. An identification and classification key for wetland types in the Lake Dakota Plain was developed for June 1975 using color infrared imagery. Wetland types in the region are now being mapped via remote sensing techniques to provide a current inventory for development of mitigation measures.

42 CFR 412.620 - Patient classification system.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 42 Public Health 2 2010-10-01 2010-10-01 false Patient classification system. 412.620 Section 412... Inpatient Rehabilitation Hospitals and Rehabilitation Units § 412.620 Patient classification system. (a) Classification methodology. (1) A patient classification system is used to classify patients in inpatient...

42 CFR 412.620 - Patient classification system.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 42 Public Health 2 2011-10-01 2011-10-01 false Patient classification system. 412.620 Section 412... Inpatient Rehabilitation Hospitals and Rehabilitation Units § 412.620 Patient classification system. (a) Classification methodology. (1) A patient classification system is used to classify patients in inpatient...

Impervious surface mapping with Quickbird imagery

PubMed Central

Lu, Dengsheng; Hetrick, Scott; Moran, Emilio

2010-01-01

This research selects two study areas with different urban developments, sizes, and spatial patterns to explore the suitable methods for mapping impervious surface distribution using Quickbird imagery. The selected methods include per-pixel based supervised classification, segmentation-based classification, and a hybrid method. A comparative analysis of the results indicates that per-pixel based supervised classification produces a large number of “salt-and-pepper” pixels, and segmentation based methods can significantly reduce this problem. However, neither method can effectively solve the spectral confusion of impervious surfaces with water/wetland and bare soils and the impacts of shadows. In order to accurately map impervious surface distribution from Quickbird images, manual editing is necessary and may be the only way to extract impervious surfaces from the confused land covers and the shadow problem. This research indicates that the hybrid method consisting of thresholding techniques, unsupervised classification and limited manual editing provides the best performance. PMID:21643434

Mars Exploration Rovers Entry, Descent, and Landing Trajectory Analysis

NASA Technical Reports Server (NTRS)

Desai, Prasun N.; Knocke, Philip C.

2007-01-01

In this study we present a novel method of land surface classification using surface-reflected GPS signals in combination with digital imagery. Two GPS-derived classification features are merged with visible image data to create terrain-moisture (TM) classes, defined here as visibly identifiable terrain or landcover classes containing a surface/soil moisture component. As compared to using surface imagery alone, classification accuracy is significantly improved for a number of visible classes when adding the GPS-based signal features. Since the strength of the reflected GPS signal is proportional to the amount of moisture in the surface, use of these GPS features provides information about the surface that is not obtainable using visible wavelengths alone. Application areas include hydrology, precision agriculture, and wetlands mapping.

Object-oriented classification using quasi-synchronous multispectral images (optical and radar) over agricultural surface

NASA Astrophysics Data System (ADS)

Marais Sicre, Claire; Baup, Frederic; Fieuzal, Remy

2015-04-01

In the context of climate change (with consequences on temperature and precipitation patterns), persons involved in agricultural management have the imperative to combine: sufficient productivity (as a response of the increment of the necessary foods) and durability of the resources (in order to restrain waste of water, fertilizer or environmental damages). To this end, a detailed knowledge of land use will improve the management of food and water, while preserving the ecosystems. Among the wide range of available monitoring tools, numerous studies demonstrated the interest of satellite images for agricultural mapping. Recently, the launch of several radar and optical sensors offer new perspectives for the multi-wavelength crop monitoring (Terrasar-X, Radarsat-2, Sentinel-1, Landsat-8…) allowing surface survey whatever the cloud conditions. Previous studies have demonstrated the interest of using multi-temporal approaches for crop classification, requiring several images for suitable classification results. Unfortunately, these approaches are limited (due to the satellite orbit cycle) and require waiting several days, week or month before offering an accurate land use map. The objective of this study is to compare the accuracy of object-oriented classification (random forest algorithm combined with vector layer coming from segmentation) to map winter crop (barley, rapeseed, grasslands and wheat) and soil states (bare soils with different surface roughness) using quasi-synchronous images. Satellite data are composed of multi-frequency and multi-polarization (HH, VV, HV and VH) images acquired near the 14th of April, 2010, over a studied area (90km²) located close to Toulouse in France. This is a region of alluvial plains and hills, which are mostly mixed farming and governed by a temperate climate. Remote sensing images are provided by Formosat-2 (04/18), Radarsat-2 (C-band, 04/15), Terrasar-X (X-band, 04/14) and ALOS (L-band, 04/14). Ground data are collected over 214 plots during the MCM'10 experiment conducted by the CESBIO laboratory in 2010. Classifications performances have been evaluated considering two cases: using only one frequency in optical or microwave domain, or using a combination of several frequencies (mixed between optical and microwave). For the first case, best results were obtained using optical wavelength with mean overall accuracy (OA) of 84%, followed by Terrasar-X (HH) and Radarsat-2 (HV or HV) which respectively offer overall accuracies of 77% and 73%. Concerning the vegetation, wheat was well classified whatever the wavelength used (OA > 93%). Barley was more complicated to classified and could be mingled with wheat or grassland. Best results were obtained using of green, red, blue, X-band or L-band wavelength offering an OA superior to 45%. Radar images were clearly well adapted to identify rapeseed (OA > 83%), especially at C (VV, HH and HV) and X-band (HH). The accuracy of grassland classification never exceeded 79% and results were stable between frequencies (excepted at L-band: 51%). The three soil roughness states were quite well classified whatever the wavelength and performances decreased with the increase of soil roughness. The combine use of multi-frequencies increased performances of the classification. Overall accuracy reached respectively 83% and 96% for C-band full polarization and for Formosat-2 multispectral approaches.

Intra- and Interobserver Reliability of Three Classification Systems for Hallux Rigidus.

PubMed

Dillard, Sarita; Schilero, Christina; Chiang, Sharon; Pham, Peter

2018-04-18

There are over ten classification systems currently used in the staging of hallux rigidus. This results in confusion and inconsistency with radiographic interpretation and treatment. The reliability of hallux rigidus classification systems has not yet been tested. The purpose of this study was to evaluate intra- and interobserver reliability using three commonly used classifications for hallux rigidus. Twenty-one plain radiograph sets were presented to ten ACFAS board-certified foot and ankle surgeons. Each physician classified each radiograph based on clinical experience and knowledge according to the Regnauld, Roukis, and Hattrup and Johnson classification systems. The two-way mixed single-measure consistency intraclass correlation was used to calculate intra- and interrater reliability. The intrarater reliability of individual sets for the Roukis and Hattrup and Johnson classification systems was "fair to good" (Roukis, 0.62±0.19; Hattrup and Johnson, 0.62±0.28), whereas the intrarater reliability of individual sets for the Regnauld system bordered between "fair to good" and "poor" (0.43±0.24). The interrater reliability of the mean classification was "excellent" for all three classification systems. Conclusions Reliable and reproducible classification systems are essential for treatment and prognostic implications in hallux rigidus. In our study, Roukis classification system had the best intrarater reliability. Although there are various classification systems for hallux rigidus, our results indicate that all three of these classification systems show reliability and reproducibility.

How to interpret rheometry, an innovative technique in soil physicochemistry, correctly - explained by critical users

NASA Astrophysics Data System (ADS)

Holthusen, Dörthe; Paulus, Eloi; Pértile, Patricia; Reichert, José Miguel; José Reinert, Dalvan; Horn, Rainer

2015-04-01

In soil physics some new methods were developed in the past years, e.g. with regard to observe soil structure non-invasively by means of micro-computed tomography, while the range of methods that investigate a soil's behavior in motion, e.g. under the impact of mechanic stresses, was enlarged by rheometry. The adjustment to the specific conditions of soil as a relatively dry and heterogeneous media opened a new field compared to the materials under investigations till then, like concrete or clay dispersions. The potential of this methodology is not fully appreciated yet which we would like to change with the help of our findings and the deduced guidelines. Rheology itself has been making part of soil science already for many years; however, the technical investigation was mostly done at a large scale, by means of triaxial shear or shear frame or compression tests etc. The corresponding measuring device, the rheometer, hence was tested and developed by and for the industries of food, cosmetics, paintings and coatings and only quite recently found to be applicable to soil also. The most interesting aspect was the possibility to combine soil physics with soil chemistry, namely to relate the behavior of soil under mechanical stresses to chemical interactions like e.g. particle charge and friction between single particles by means of an amplitude sweep test. Meanwhile, many different soils of different texture, organic matter and oxides and hydroxides content, and fertilization levels have been investigated at different matric potentials and allowed for a comparatively broad classification system. Therewith, the microstructural stability of a given soil by means of stiffness degradation during an amplitude sweep test can be categorized as a function of texture and matric potential. The micro scale soil stability furthermore influences the processes and thus soil structural stability at larger scales, which supports the investigations of relationships between different scales. Transferability to field situations is given due to the character of the mechanic stress which equals those appearing e.g. under a tractor tire exerting vibrating, compressing and shearing forces. Unfortunately, the multiple results of this single test can impede the use of rheometry as their interpretation requires intensive data analysis. By pointing out the single results and their meaning for soil structure, we aim at facilitating the use of rheometry. We also suggest moderate alterations to take into account more strongly the vertical compression of soil for a more comprehensive implementation of a micro shear test. Additionally, we point out further uses of a rheometer in soil physics, which is the viscosity, i. e. the ability of a fluid to penetrate into a porous system and to be relocated within. Herewith, quite complex fluid characteristics, e.g. of animal manure, anaerobic digestates, but also pesticides in aqueous solution, root mucilage etc. can be determined and applied as improved, because more detailed, model parameters in soil water transport. As a conclusion, our contribution aims at further promoting a promising method for investigating the fundamentals of soil physics at the interface to soil chemistry.

Rainfall and human activity impacts on soil losses and rill erosion in vineyards (Ruwer Valley, Germany)

NASA Astrophysics Data System (ADS)

Rodrigo Comino, J.; Brings, C.; Lassu, T.; Iserloh, T.; Senciales, J. M.; Martínez Murillo, J. F.; Ruiz Sinoga, J. D.; Seeger, M.; Ries, J. B.

2015-07-01

Vineyards are one of the eco-geomorphological systems most conditioned by human activity in Germany. The vineyards of the Ruwer Valley (Germany) are characterized by high soil erosion rates and rill problems on steep slopes (between 23 and 26°) caused by the increasingly frequent heavy rainfall events as well as deterioration due to incorrect land use managements. The objective of this paper is to determine and to quantify the hydrological and erosive phenomena in one vineyard in Germany during different seasons and under different management conditions (before, during and after vintage). For this purpose, a combined methodology was applied. Climatic (rainfall depth distributions and return periods), pedological (soil analysis and classification), geomorphological (sediment movements and rills evolution) and biological (botanic marks on the vines) variables were used on the two experimental plots in the village of Waldrach (Trier, region of Rhineland-Palatinate). The results showed high infiltration rates (near 100 %) and subsurface flow which were detected by rainfall simulations performed at different times of the year (between September and December). The highest variations of the monitored rills (lateral and frontal movements) were noted before and during vintage, when footsteps occurred concentrated during a short period of time (between September and October). Finally, two maps of soil loss were generated, indicated by botanic marks on the graft union of the vines. 62.5 t ha-1 yr-1 soil loss was registered in the experimental plots of the new vineyards (2 years), while 3.4 t ha-1 yr-1 was recorded in the old one (35 years).

Effects of gross motor function and manual function levels on performance-based ADL motor skills of children with spastic cerebral palsy.

PubMed

Park, Myoung-Ok

2017-02-01

[Purpose] The purpose of this study was to determine effects of Gross Motor Function Classification System and Manual Ability Classification System levels on performance-based motor skills of children with spastic cerebral palsy. [Subjects and Methods] Twenty-three children with cerebral palsy were included. The Assessment of Motor and Process Skills was used to evaluate performance-based motor skills in daily life. Gross motor function was assessed using Gross Motor Function Classification Systems, and manual function was measured using the Manual Ability Classification System. [Results] Motor skills in daily activities were significantly different on Gross Motor Function Classification System level and Manual Ability Classification System level. According to the results of multiple regression analysis, children categorized as Gross Motor Function Classification System level III scored lower in terms of performance based motor skills than Gross Motor Function Classification System level I children. Also, when analyzed with respect to Manual Ability Classification System level, level II was lower than level I, and level III was lower than level II in terms of performance based motor skills. [Conclusion] The results of this study indicate that performance-based motor skills differ among children categorized based on Gross Motor Function Classification System and Manual Ability Classification System levels of cerebral palsy.

Alpine Soils as long-term Bioindicators

NASA Astrophysics Data System (ADS)

Nestroy, O.

2009-04-01

Alpine soils as long-term bioindicators The introductory words concern the definitions and peculiarities of alpine soils and their position in the Austrian Soil Classification 2000 in comparison with the World Reference Base for Soil Resources 2006. The important parameters for genesis and threats for these soils in steep and high positions are discussed. It must be emphasized that the main threats are the very different kinds of erosion e.g. by water, wind and snow, and also by skiing (end of season) as well as and mountain-biking (mainly summer-sport). Due the very slow regeneration and - in this connection - due to the very slow changes of the soil entities, these soils give an utmost importance as a long-time bioindicator. With regard to the climate change one can assume an increase in the content of organic matter on site, but also an increase of erosion and mass movement on the other site, e. g. in kind of "plaiken" (soil slide) as result of an increasing intensity of rainfall. It lies partly in our hands to diminish the number and the intensity of the threats, we can influence the soil development, but the result to reach a new ecological equilibrium is very long - in case of alpine soil more than two generations.

78 FR 18252 - Prevailing Rate Systems; North American Industry Classification System Based Federal Wage System...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-26

...-AM78 Prevailing Rate Systems; North American Industry Classification System Based Federal Wage System... 2007 North American Industry Classification System (NAICS) codes currently used in Federal Wage System... (OPM) issued a final rule (73 FR 45853) to update the 2002 North American Industry Classification...

Restoration of contaminated soils in abandoned mine areas (Tuscany, Italy)

NASA Astrophysics Data System (ADS)

Bini, Claudio; Wahsha, Mohammad

2016-04-01

In Italy ore research and exploitation have been nearly exhausted since the end of the last century, and have left on the land a huge amount of mine waste, therefore provoking evident environmental damage including surface and groundwater, soils, vegetation and the food chain, and a potential threat to human health. The main processes occurring at these sites are: rock disgregation, fragments migration, dust dispersion, oxidation (Eh>250mV), acidification (pH<7), hydrolisis and metal leaching, precipitation of oxides and sulphates. The restoration of these sites, therefore, is a primary objective, in order to reduce/eliminate the risk associated to the contamination sources of past activities, and the consequent environmental and human health hazard. The increasing environmental consciousness of general population compelled Public Administrators to set down effective legislation acts on this subject (e.g. D.L. 152/2006), and more generally on environmental contamination. In this work we present the results of a survey carried out at several mixed sulphides mine sites in Tuscany, exploited for at least a millennium, and closed in the last century. Biogeochemical analyses carried out on representative soil profiles (Spolic Technosols) and vegetation in the proximal and distal areas of ore exploitation show heavy metal concentrations (Cd, Cu, Fe, Pb, Zn) overcoming legislation limits on average. Ni, Cr and Mn concentrations, instead, are generally below the reference levels. The results obtained suggest that the abandoned mine sites represent actual natural laboratories where to experiment new opportunities for restoration of anthropogenically contaminated areas, and to study new pedogenetic trends from these peculiar parent materials. Moreover, plants growing on these substrates are genetically adapted to metal-enriched soils, and therefore may be utilized in phytoremediation of contaminated sites. Furthermore, the institution of natural parks in these areas could enhance their educational and scientific value, contributing in the meantime to general population amusement and recreation. Finally, it is the occasion for soil scientists to submit to the scientific community new classification proposals of this new kind of soils. Key-words: mine waste, heavy metals, phytoremediation, soil genesis, soil classification

Midwest Climate and Agriculture - Monitoring Tillage Practices with NASA Remote Sensors

NASA Astrophysics Data System (ADS)

Makar, N. I.; Archer, S.; Rooks, K.; Sparks, K.; Trigg, C.; Lourie, J.; Wilkins, K.

2011-12-01

Concerns about climate change have driven efforts to reduce or offset greenhouse gas emissions. Agricultural activity has drawn considerable attention because it accounts for nearly twelve percent of total anthropogenic emissions. Depending on the type of tillage method utilized, farm land can be either a source or a sink of carbon. Conventional tillage disturbs the soil and can release greenhouse gases into the atmosphere. Conservational tillage practices have been advocated for their ability to sequester carbon, reduce soil erosion, maintain soil moisture, and increase long-term productivity. If carbon credit trading systems are implemented, a cost-effective, efficient tillage monitoring system is needed to enforce offset standards. Remote sensing technology can expedite the process and has shown promising results in distinguishing crop residue from soil. Agricultural indices such as the CAI, SINDRI, and LCA illuminate the unique reflectance spectra of crop residue and are thus able to classify fields based on percent crop cover. The CAI requires hyperspectral data, as it relies on narrow bands within the shortwave infrared portion of the electromagnetic spectrum. Although limited in availability, hyperspectral data has been shown to produce the most accurate results for detecting crop residue on the soil. A new approach to using the CAI was the focus of this study. Previously acquired field data was located in a region covered by a Hyperion swath and is thus the primary study area. In previous studies, ground-based data were needed for each satellite swath to correctly calibrate the linear relationship between the index values and the fraction of residue cover. We hypothesized that there should be a standard method which is able to convert index values into residue classifications without ground data analysis. To do this, end index values for a particular data set were assumed to be associated with end values of residue cover percentages. This method may prove to be more practical for end-users such as the USDA to quickly assess residue cover in a given region.

Automatic 3D Extraction of Buildings, Vegetation and Roads from LIDAR Data

NASA Astrophysics Data System (ADS)

Bellakaout, A.; Cherkaoui, M.; Ettarid, M.; Touzani, A.

2016-06-01

Aerial topographic surveys using Light Detection and Ranging (LiDAR) technology collect dense and accurate information from the surface or terrain; it is becoming one of the important tools in the geosciences for studying objects and earth surface. Classification of Lidar data for extracting ground, vegetation, and buildings is a very important step needed in numerous applications such as 3D city modelling, extraction of different derived data for geographical information systems (GIS), mapping, navigation, etc... Regardless of what the scan data will be used for, an automatic process is greatly required to handle the large amount of data collected because the manual process is time consuming and very expensive. This paper is presenting an approach for automatic classification of aerial Lidar data into five groups of items: buildings, trees, roads, linear object and soil using single return Lidar and processing the point cloud without generating DEM. Topological relationship and height variation analysis is adopted to segment, preliminary, the entire point cloud preliminarily into upper and lower contours, uniform and non-uniform surface, non-uniform surfaces, linear objects, and others. This primary classification is used on the one hand to know the upper and lower part of each building in an urban scene, needed to model buildings façades; and on the other hand to extract point cloud of uniform surfaces which contain roofs, roads and ground used in the second phase of classification. A second algorithm is developed to segment the uniform surface into buildings roofs, roads and ground, the second phase of classification based on the topological relationship and height variation analysis, The proposed approach has been tested using two areas : the first is a housing complex and the second is a primary school. The proposed approach led to successful classification results of buildings, vegetation and road classes.

Biochar carbon sequestration and downward translocation in contrasting soils under field conditions in Australia

NASA Astrophysics Data System (ADS)

Pal Singh, Bhupinder; Fang, Yunying; Boersma, Mark; Matta, Pushpinder; Van Zwieten, Lukas; Macdonald, Lynne

2014-05-01

Carbon (C) sequestration potential of biochar depends on its stability and stabilisation of native or added organic C in soil. However, the processes of biochar degradation, fate in soil organic matter pools, and downward translocation in the soil profile, and the influence of biochar on emissions or stabilisation of native organic C sources are poorly understood under field conditions. An Eucalyptus saligna green-waste biochar (δ13C -36.6o; total C 66.8%) produced by slow pyrolysis at 450° C was applied at 29.2 t ha-1 to 10-cm depth in circular (0.66-m diameter) micro-plots, encompassing three soils [Tenosol, Dermosol and Ferrosol (Australian Soil Classification); Arenosol, Planosol, Ferralsol (approximate WRB Classification] under contrasting pasture systems across New South Wales and Tasmania (Australia). The aims of this study were to (i) monitor the fate of biochar C in respired CO2 and quantify biochar stability and stabilisation under field conditions, (ii) determine the influence of biochar on native soil C emissions, and (iii) track downward migration of the surface (0-10 cm) applied biochar over a 1-year period. We also periodically monitored the impact of biochar on microbial biomass carbon (MBC) and aboveground biomass production. The soils were separated into light and heavy C fractions and the C recovery of applied biochar C was calculated at 0-8, 8-12, 12-20 and 20-30 cm depths. Biochar C mineralisation rates were generally higher, albeit fluctuated widely, in the first 3 to 4 months. Over the first 7 months, the proportion of added biochar C mineralised in soils ranged between 1.4 and 5.5% and followed the sequence: Tenosol < Dermosol < Ferrosol. The mean residence time (MRT) of biochar ranged from 29 and 70 years. These values of MRT should be treated as highly conservative values, as they mainly reflect the MRT of relatively labile C components in biochar. The cumulative CO2-C emission over the 7-month period from native soil and plant sources was larger in the biochar-amended Tenosol, whereas lower in the biochar-amended Dermosol and Ferrosol, relative to the corresponding controls. As the aboveground biomass production was similar between the biochar-amended and control micro-plots during the first 7 months, the higher cumulative CO2-C emission in the biochar versus control Tenosol may be related to positive priming of native SOC mineralisation by biochar, and/or greater belowground allocation of plant-assimilated C, or possibly alternative effects (i.e. negative priming or lower belowground plant C allocation) in the Dermosol and Ferrosol. At 4 months, most of the applied biochar was recovered in the top 12 cm depth, with the total recovery of 72.1% in the Tenosol, 103.7% in the Dermosol and 79.2% in the Ferrosol. Biochar C was clearly migrated downward from the application depth (0-10 cm) within 4 months, particularly in Tenosol and Ferrosol, with the recovery of 4.8%, 2.7% and 12.7% in the 12-20 cm profile, and 6.0%, 1.1% and 9.1% at the 20-30 cm profile, across the Tenosol, Dermosol and Ferrosol, respectively. At 4 months, MBC was higher in the biochar-amended Tenosol and Dermosol than the corresponding controls, whereas, biochar had no effect on MBC in the Ferrosol, possibly due to its higher native organic C content cf. the other soil types. The updated results will be presented at the conference.

Designation of less favorable areas by the regionalization of soil degradation on various spatial scales

NASA Astrophysics Data System (ADS)

Pásztor, L.; Szabó, J.; Bakacsi, Zs.; Laborczi, A.

2009-04-01

One of the main objectives of the EU's Common Agricultural Policy is to encourage maintaining agricultural production in less favorable areas (LFA) in order (among others) to sustain agricultural production and use natural resources, in such a way to secure both stable production and income to farmers and to protect the environment. LFA assignment has both ecological and severe economical aspects. Delimitation of LFAs can be carried out by using biophysical diagnostic criteria on low soil productivity and poor climate conditions. Identification of low-productivity areas requires regionalization of soil functions related to food and other biomass production. This process can be carried out in different scales from national to local level, but always requires map-based pedological and further environmental information with appropriate spatial resolution. For the regionalization of less productive areas in national scale a functional approach was used which integrates the knowledge on soil degradation processes in nationwide level. Specific soil threats were classified into ranked categories. Supposing (quasi)uniform distribution of vulnerability measure along these classes, we introduced a "standardized" value as a ratio of the class order to the maximum class order expressed in percentage. For the overall spatial characterization of degradation status, spatial information was integrated in a result map by summarizing the degradation specific "standardized" cell values. This map in one hand has been used for the delineation of soil degradation regions. On the other hand appropriate spatial aggregation of index values on geographical and administrative regions is suitable for their quantitative comparison thus they can be ranked and this feature can be used for the identification of less favorable areas. At the more detailed, county level the Digital Kreybig Soil Information System was used as a tool of the regionalization of soil functions related to soil productivity. Concurrent spatial analysis of the suitability of soils for agricultural use and their sensitivity to physical and chemical degradation were carried out which resulted in a so-called ecotype-based characterization of land. As a spin-off, this classification was used for the designation of low productive areas suitable for hypogenous and cap fungi plantations as landuse alternative for croplands.

Mapping ecological states in a complex environment

NASA Astrophysics Data System (ADS)

Steele, C. M.; Bestelmeyer, B.; Burkett, L. M.; Ayers, E.; Romig, K.; Slaughter, A.

2013-12-01

The vegetation of northern Chihuahuan Desert rangelands is sparse, heterogeneous and for most of the year, consists of a large proportion of non-photosynthetic material. The soils in this area are spectrally bright and variable in their reflectance properties. Both factors provide challenges to the application of remote sensing for estimating canopy variables (e.g., leaf area index, biomass, percentage canopy cover, primary production). Additionally, with reference to current paradigms of rangeland health assessment, remotely-sensed estimates of canopy variables have limited practical use to the rangeland manager if they are not placed in the context of ecological site and ecological state. To address these challenges, we created a multifactor classification system based on the USDA-NRCS ecological site schema and associated state-and-transition models to map ecological states on desert rangelands in southern New Mexico. Applying this system using per-pixel image processing techniques and multispectral, remotely sensed imagery raised other challenges. Per-pixel image classification relies upon the spectral information in each pixel alone, there is no reference to the spatial context of the pixel and its relationship with its neighbors. Ecological state classes may have direct relevance to managers but the non-unique spectral properties of different ecological state classes in our study area means that per-pixel classification of multispectral data performs poorly in discriminating between different ecological states. We found that image interpreters who are familiar with the landscape and its associated ecological site descriptions perform better than per-pixel classification techniques in assigning ecological states. However, two important issues affect manual classification methods: subjectivity of interpretation and reproducibility of results. An alternative to per-pixel classification and manual interpretation is object-based image analysis. Object-based image analysis provides a platform for classification that more closely resembles human recognition of objects within a remotely sensed image. The analysis presented here compares multiple thematic maps created for test locations on the USDA-ARS Jornada Experimental Range ranch. Three study sites in different pastures, each 300 ha in size, were selected for comparison on the basis of their ecological site type (';Clayey', ';Sandy' and a combination of both) and the degree of complexity of vegetation cover. Thematic maps were produced for each study site using (i) manual interpretation of digital aerial photography (by five independent interpreters); (ii) object-oriented, decision-tree classification of fine and moderate spatial resolution imagery (Quickbird; Landsat Thematic Mapper) and (iii) ground survey. To identify areas of uncertainty, we compared agreement in location, areal extent and class assignation between 5 independently produced, manually-digitized ecological state maps and with the map created from ground survey. Location, areal extent and class assignation of the map produced by object-oriented classification was also assessed with reference to the ground survey map.

In-situ soil sensing for planetary micro-rovers with hybrid wheel-leg systems

NASA Astrophysics Data System (ADS)

Comin Cabrera, Francisco Jose

Rover missions exploring other planets are tightly constrained regarding the trade-off between safety and traversal speed. Detecting and avoiding hazards during navigation is capital to preserve the mobility of a rover. Low traversal speeds are often enforced to assure that wheeled rovers do not become stuck in challenging terrain, hindering the performance and scientific return of the mission. Even such precautions do not guarantee safe navigation due to non-geometric hazards hidden in the terrain, such as sand traps beneath thin duricrusts. These issues motivate the research of the interaction with rough and sandy planetary terrains of conventional and innovative robot locomotion concepts. Hybrid wheel-legs combine the mechanical and control simplicity of wheeled locomotion with the enhanced mobility of legged locomotion. This concept has been rarely proposed for planetary exploration and the study of its interaction with granular terrains is at a very early stage. This research focuses on advancing the state-of-the-art of wheel-leg-soil interaction analysis and applying it through in-situ sensing to simultaneously improve the speed and safety of planetary rover missions. The semi-empirical approach used combines both theoretical modelling and experimental analysis of data obtained in laboratory and field analogues. A novel light-weight, low-power sensor system, capable of reliably detecting wheel-leg sinkage and slippage phenomena on-the-fly, is designed, implemented and tested both as part of a simplified single-wheel-leg test bed and integrated in a fully mobile micro-rover. Moreover, existing analytical models for the interaction between deformable terrain and heavily-loaded wheels or lightly-loaded legs are adapted to the generalised medium-loaded multi-legged wheel-leg case and combined into hybrid approaches for better accuracy, as validated against experimental data. Finally, the soil sensor system and analytical models proposed are used to develop and prove the effectiveness of different solutions for soil characterisation, trafficability assessment and terrain classification based on non-geometric physical properties.

Stream classification of the Apalachicola-Chattahoochee-Flint River System to support modeling of aquatic habitat response to climate change

USGS Publications Warehouse

Elliott, Caroline M.; Jacobson, Robert B.; Freeman, Mary C.

2014-01-01

A stream classification and associated datasets were developed for the Apalachicola-Chattahoochee-Flint River Basin to support biological modeling of species response to climate change in the southeastern United States. The U.S. Geological Survey and the Department of the Interior’s National Climate Change and Wildlife Science Center established the Southeast Regional Assessment Project (SERAP) which used downscaled general circulation models to develop landscape-scale assessments of climate change and subsequent effects on land cover, ecosystems, and priority species in the southeastern United States. The SERAP aquatic and hydrologic dynamics modeling efforts involve multiscale watershed hydrology, stream-temperature, and fish-occupancy models, which all are based on the same stream network. Models were developed for the Apalachicola-Chattahoochee-Flint River Basin and subbasins in Alabama, Florida, and Georgia, and for the Upper Roanoke River Basin in Virginia. The stream network was used as the spatial scheme through which information was shared across the various models within SERAP. Because these models operate at different scales, coordinated pair versions of the network were delineated, characterized, and parameterized for coarse- and fine-scale hydrologic and biologic modeling. The stream network used for the SERAP aquatic models was extracted from a 30-meter (m) scale digital elevation model (DEM) using standard topographic analysis of flow accumulation. At the finer scale, reaches were delineated to represent lengths of stream channel with fairly homogenous physical characteristics (mean reach length = 350 m). Every reach in the network is designated with geomorphic attributes including upstream drainage basin area, channel gradient, channel width, valley width, Strahler and Shreve stream order, stream power, and measures of stream confinement. The reach network was aggregated from tributary junction to tributary junction to define segments for the benefit of hydrological, soil erosion, and coarser ecological modeling. Reach attributes are summarized for each segment. In six subbasins segments are assigned additional attributes about barriers (usually impoundments) to fish migration and stream isolation. Segments in the six sub-basins are also attributed with percent urban area for the watershed upstream from the stream segment for each decade from 2010–2100 from models of urban growth. On a broader scale, for application in a coarse-scale species-response model, the stream-network information is aggregated and summarized by 256 drainage subbasins (Hydrologic Response Units) used for watershed hydrologic and stream-temperature models. A model of soil erodibility based on the Revised Universal Soil Loss Equation also was developed at this scale to parameterize a model to evaluate stream condition. The reach-scale network was classified using multivariate clustering based on modeled channel width, valley width, and mean reach gradient as variables. The resulting classification consists of a 6-cluster and a 12-cluster classification for every reach in the Apalachicola-Chattahoochee-Flint Basin. We present an example of the utility of the classification that was tested using the occurrence of two species of darters and two species of minnows in the Apalachicola-Chattahoochee-Flint River Basin, the blackbanded darter and Halloween darter, and the bluestripe shiner and blacktail shiner.

Impact of Soil Texture on Soil Ciliate Communities

NASA Astrophysics Data System (ADS)

Chau, J. F.; Brown, S.; Habtom, E.; Brinson, F.; Epps, M.; Scott, R.

2014-12-01

Soil water content and connectivity strongly influence microbial activities in soil, controlling access to nutrients and electron acceptors, and mediating interactions between microbes within and between trophic levels. These interactions occur at or below the pore scale, and are influenced by soil texture and structure, which determine the microscale architecture of soil pores. Soil protozoa are relatively understudied, especially given the strong control they exert on bacterial communities through predation. Here, ciliate communities in soils of contrasting textures were investigated. Two ciliate-specific primer sets targeting the 18S rRNA gene were used to amplify DNA extracted from eight soil samples collected from Sumter National Forest in western South Carolina. Primer sets 121F-384F-1147R (semi-nested) and 315F-959R were used to amplify soil ciliate DNA via polymerase chain reaction (PCR), and the resulting PCR products were analyzed by gel electrophoresis to obtain quantity and band size. Approximately two hundred ciliate 18S rRNA sequences were obtained were obtained from each of two contrasting soils. Sequences were aligned against the NCBI GenBank database for identification, and the taxonomic classification of best-matched sequences was determined. The ultimate goal of the work is to quantify changes in the ciliate community under short-timescale changes in hydrologic conditions for varying soil textures, elucidating dynamic responses to desiccation stress in major soil ciliate taxa.

Teaching Soil Science in Primary and Secondary Schools

NASA Technical Reports Server (NTRS)

Levine, Elissa R.

1998-01-01

Earth's thin layer of soil is a fragile resource, made up of minerals, organic materials, air, water, and billions of living organisms. Soils plays a variety of critical roles that sustain life on Earth. If we think about soil, we tend to see it first as the source of most of the food we eat and the fibers we use, such as wood and cotton. Few students realize that soils also provide the key ingredients to many of the medicines (including antibiotics), cosmetics, and dyes that we use. Fewer still understand the importance of soils in integrating, controlling, and regulating the movement of air, water, materials, and energy between the hydrosphere, lithosphere, atmosphere, and biosphere. Because soil sustains life, it offers both a context and a natural laboratory for investigating these interactions. The enclosed poster, which integrates soil profiles with typical landscapes in which soils form, can also help students explore the interrelationships of Earth systems and gain an understanding of our soil resources. The poster, produced jointly by the American Geological Institute and the Soil Science Society of America, aims to increase awareness of the importance of soil, as does the GLOBE (Global Learning and Observations To Benefit the Environment) Program. Vice President Al Gore instituted the GLOBE Program on Earth Day of 1993 to increase environmental awareness of individuals throughout the world, contribute to a better scientific understanding of the Earth, and help all students reach higher levels of achievement in science and mathematics. GLOBE functions as a partnership between scientists, students, and teachers in which scientists design protocols for specific measurements they need for their research that can be performed by K-12 students. Teachers are trained in the GLOBE protocols and teach them to their students. Students make the measurements, enter data via the Internet to a central data archive, and the data becomes available to scientists and the general community. Students benefit by having a "hands-on"experience in science, math, and technology, using their local environment as a learning laboratory, as well as contact with scientists and other students around the world. Soil investigations have become an essential component of GLOBE. The protocols that have been developed so far within the GLOBE program include GPS Location, Atmosphere/Climate, Soil Characterization, Soil Moisture and Temperature, Land Cover/Biometry, Hydrology, and Satellite Image Classification. For the GLOBE Soil Characterization Protocol, students explore the physical. chemical, and morphological properties of the soil at their study site. They are asked to dig a pit or use an auger to about 1 meter at at least 2 sites.

Progress in coherent laser radar

NASA Technical Reports Server (NTRS)

Vaughan, J. M.

1986-01-01

Considerable progress with coherent laser radar has been made over the last few years, most notably perhaps in the available range of high performance devices and components and the confidence with which systems may now be taken into the field for prolonged periods of operation. Some of this increasing maturity was evident at the 3rd Topical Meeting on Coherent Laser Radar: Technology and Applications. Topics included in discussions were: mesoscale wind fields, nocturnal valley drainage and clear air down bursts; airborne Doppler lidar studies and comparison of ground and airborne wind measurement; wind measurement over the sea for comparison with satellite borne microwave sensors; transport of wake vortices at airfield; coherent DIAL methods; a newly assembled Nd-YAG coherent lidar system; backscatter profiles in the atmosphere and wavelength dependence over the 9 to 11 micrometer region; beam propagation; rock and soil classification with an airborne 4-laser system; technology of a global wind profiling system; target calibration; ranging and imaging with coherent pulsed and CW system; signal fluctuations and speckle. Some of these activities are briefly reviewed.

Understanding the use of standardized nursing terminology and classification systems in published research: A case study using the International Classification for Nursing Practice(®).

PubMed

Strudwick, Gillian; Hardiker, Nicholas R

2016-10-01

In the era of evidenced based healthcare, nursing is required to demonstrate that care provided by nurses is associated with optimal patient outcomes, and a high degree of quality and safety. The use of standardized nursing terminologies and classification systems are a way that nursing documentation can be leveraged to generate evidence related to nursing practice. Several widely-reported nursing specific terminologies and classifications systems currently exist including the Clinical Care Classification System, International Classification for Nursing Practice(®), Nursing Intervention Classification, Nursing Outcome Classification, Omaha System, Perioperative Nursing Data Set and NANDA International. However, the influence of these systems on demonstrating the value of nursing and the professions' impact on quality, safety and patient outcomes in published research is relatively unknown. This paper seeks to understand the use of standardized nursing terminology and classification systems in published research, using the International Classification for Nursing Practice(®) as a case study. A systematic review of international published empirical studies on, or using, the International Classification for Nursing Practice(®) were completed using Medline and the Cumulative Index for Nursing and Allied Health Literature. Since 2006, 38 studies have been published on the International Classification for Nursing Practice(®). The main objectives of the published studies have been to validate the appropriateness of the classification system for particular care areas or populations, further develop the classification system, or utilize it to support the generation of new nursing knowledge. To date, most studies have focused on the classification system itself, and a lesser number of studies have used the system to generate information about the outcomes of nursing practice. Based on the published literature that features the International Classification for Nursing Practice, standardized nursing terminology and classification systems appear to be well developed for various populations, settings and to harmonize with other health-related terminology systems. However, the use of the systems to generate new nursing knowledge, and to validate nursing practice is still in its infancy. There is an opportunity now to utilize the well-developed systems in their current state to further what is know about nursing practice, and how best to demonstrate improvements in patient outcomes through nursing care. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

[Application of hyper-spectral remote sensing technology in environmental protection].

PubMed

Zhao, Shao-Hua; Zhang, Feng; Wang, Qiao; Yao, Yun-Jun; Wang, Zhong-Ting; You, Dai-An

2013-12-01

Hyper-spectral remote sensing (RS) technology has been widely used in environmental protection. The present work introduces its recent application in the RS monitoring of pollution gas, green-house gas, algal bloom, water quality of catch water environment, safety of drinking water sources, biodiversity, vegetation classification, soil pollution, and so on. Finally, issues such as scarce hyper-spectral satellites, the limits of data processing and information extract are related. Some proposals are also presented, including developing subsequent satellites of HJ-1 satellite with differential optical absorption spectroscopy, greenhouse gas spectroscopy and hyper-spectral imager, strengthening the study of hyper-spectral data processing and information extraction, and promoting the construction of environmental application system.

Sorption characteristics of cadmium in a clay soil of Mae Ku creek, Tak Province, Thailand

NASA Astrophysics Data System (ADS)

Thunyawatcharakul, P.; Chotpantarat, S.

2018-05-01

Mae Sot is a district in Tak province, the northern part of Thailand where has encountered with cadmium (Cd) contaminated in soils. Exposure of Cd can lead to severe health effect, for examples, bone softening, osteoporosis, renal dysfunction, and Itai-Itai disease. This study aims at elucidating sorption behavior of Cd in the contaminated soil collected from Mae Ku creek, Mae Sot district, Thailand. Batch sorption experiment was conducted in order to investigate sorption characteristics of Cd onto the contaminated soil. The soil sample taken from the study area consists of 26% sand, 16% silt 58% clay, which categorized as a clay soil, based on USDA classification. Soil pH is slightly alkaline (pH∼7.7) and organic matter in the soil is 2.93%. The initial concentration in the batch sorption experiment was in the range from 0- 200 ppm. The result from the batch sorption experiment showed that soil sample can adsorb Cd up to 173.5 ppm and the sorption behavior of the soil sample can be well described by Freundlich isotherm, indicating the multilayer sorption (R2 = 0.9964), with Freundlich constants of 0.312 and 1.760 L g-1 for 1/n and Kf, respectively.

Application of portable XRF and VNIR sensors for rapid assessment of soil heavy metal pollution.

PubMed

Hu, Bifeng; Chen, Songchao; Hu, Jie; Xia, Fang; Xu, Junfeng; Li, Yan; Shi, Zhou

2017-01-01

Rapid heavy metal soil surveys at large scale with high sampling density could not be conducted with traditional laboratory physical and chemical analyses because of the high cost, low efficiency and heavy workload involved. This study explored a rapid approach to assess heavy metals contamination in 301 farmland soils from Fuyang in Zhejiang Province, in the southern Yangtze River Delta, China, using portable proximal soil sensors. Portable X-ray fluorescence spectroscopy (PXRF) was used to determine soil heavy metals total concentrations while soil pH was predicted by portable visible-near infrared spectroscopy (PVNIR). Zn, Cu and Pb were successfully predicted by PXRF (R2 >0.90 and RPD >2.50) while As and Ni were predicted with less accuracy (R2 <0.75 and RPD <1.40). The pH values were well predicted by PVNIR. Classification of heavy metals contamination grades in farmland soils was conducted based on previous results; the Kappa coefficient was 0.87, which showed that the combination of PXRF and PVNIR was an effective and rapid method to determine the degree of pollution with soil heavy metals. This study provides a new approach to assess soil heavy metals pollution; this method will facilitate large-scale surveys of soil heavy metal pollution.

Application of portable XRF and VNIR sensors for rapid assessment of soil heavy metal pollution

PubMed Central

Hu, Bifeng; Chen, Songchao; Hu, Jie; Xia, Fang; Xu, Junfeng; Li, Yan; Shi, Zhou

2017-01-01

Rapid heavy metal soil surveys at large scale with high sampling density could not be conducted with traditional laboratory physical and chemical analyses because of the high cost, low efficiency and heavy workload involved. This study explored a rapid approach to assess heavy metals contamination in 301 farmland soils from Fuyang in Zhejiang Province, in the southern Yangtze River Delta, China, using portable proximal soil sensors. Portable X-ray fluorescence spectroscopy (PXRF) was used to determine soil heavy metals total concentrations while soil pH was predicted by portable visible-near infrared spectroscopy (PVNIR). Zn, Cu and Pb were successfully predicted by PXRF (R2 >0.90 and RPD >2.50) while As and Ni were predicted with less accuracy (R2 <0.75 and RPD <1.40). The pH values were well predicted by PVNIR. Classification of heavy metals contamination grades in farmland soils was conducted based on previous results; the Kappa coefficient was 0.87, which showed that the combination of PXRF and PVNIR was an effective and rapid method to determine the degree of pollution with soil heavy metals. This study provides a new approach to assess soil heavy metals pollution; this method will facilitate large-scale surveys of soil heavy metal pollution. PMID:28234944

Can ecological land classification increase the utility of vegetation monitoring data

USDA-ARS?s Scientific Manuscript database

Vegetation dynamics in rangelands and other ecosystems are known to be mediated by topoedaphic properties. Vegetation monitoring programs, however, often do not consider the impact of soils and other sources of landscape heterogeneity on the temporal patterns observed. Ecological sites (ES) comprise...